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1,611
car_retails
bird:train.json:1655
How many 2003 Harley-Davidson Eagle Drag Bikes were ordered?
SELECT SUM(t2.quantityOrdered) FROM products AS t1 INNER JOIN orderdetails AS t2 ON t1.productCode = t2.productCode WHERE t1.productName = '2003 Harley-Davidson Eagle Drag Bike'
[ "How", "many", "2003", "Harley", "-", "Davidson", "Eagle", "Drag", "Bikes", "were", "ordered", "?" ]
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[ "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "B-TABLE", "O" ]
1,613
professional_basketball
bird:train.json:2861
What is the name of the team with the highest home lost rate?
SELECT name FROM teams ORDER BY CAST(homeWon AS REAL) / (homeWon + homeLost) DESC LIMIT 1
[ "What", "is", "the", "name", "of", "the", "team", "with", "the", "highest", "home", "lost", "rate", "?" ]
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1,614
sales
bird:train.json:5431
Among customers named Kate, who has the highest quantity?
SELECT T2.FirstName, T2.LastName FROM Sales AS T1 INNER JOIN Customers AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.FirstName = 'Kate' ORDER BY T1.Quantity DESC LIMIT 1
[ "Among", "customers", "named", "Kate", ",", "who", "has", "the", "highest", "quantity", "?" ]
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[ "O", "B-TABLE", "B-COLUMN", "B-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
1,615
hockey
bird:train.json:7733
Which year recorded the most number of goals by a player and how old was the player at the time the most number of goals was achieved by him?
SELECT T1.year, T1.year - T2.birthYear FROM Scoring AS T1 INNER JOIN Master AS T2 ON T1.playerID = T2.playerID GROUP BY T1.year, T1.year - T2.birthYear ORDER BY SUM(T1.G) DESC LIMIT 1
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[ { "id": 3, "type": "column", "value": "birthyear" }, { "id": 4, "type": "column", "value": "playerid" }, { "id": 1, "type": "table", "value": "scoring" }, { "id": 2, "type": "table", "value": "master" }, { "id": 0, "type": "column", "value"...
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1,616
world_development_indicators
bird:train.json:2183
Which country have conducted population census from 2010 until 2012 and have completed vital registration?
SELECT ShortName, LongName FROM Country WHERE LatestPopulationCensus >= 2010 AND LatestPopulationCensus < 2013 AND VitalRegistrationComplete = 'Yes'
[ "Which", "country", "have", "conducted", "population", "census", "from", "2010", "until", "2012", "and", "have", "completed", "vital", "registration", "?" ]
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1,617
hospital_1
spider:train_spider.json:3973
Which physicians are trained in procedures that are more expensive than 5000?
SELECT T1.name FROM physician AS T1 JOIN trained_in AS T2 ON T1.employeeid = T2.physician JOIN procedures AS T3 ON T3.code = T2.treatment WHERE T3.cost > 5000
[ "Which", "physicians", "are", "trained", "in", "procedures", "that", "are", "more", "expensive", "than", "5000", "?" ]
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[ "O", "B-COLUMN", "O", "B-TABLE", "I-TABLE", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
1,618
university
bird:train.json:8087
Give the id of "Center for World University Rankings".
SELECT id FROM ranking_system WHERE system_name = 'Center for World University Rankings'
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-TABLE", "O", "O" ]
1,619
boat_1
bird:test.json:893
Find the number of reservations for each boat.
SELECT bid , count(*) FROM Reserves GROUP BY bid
[ "Find", "the", "number", "of", "reservations", "for", "each", "boat", "." ]
[ { "id": 0, "type": "table", "value": "reserves" }, { "id": 1, "type": "column", "value": "bid" } ]
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[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
1,620
hockey
bird:train.json:7801
State the player ID and coach ID of person who have become coach after retirement.
SELECT playerID, coachID FROM Master WHERE playerID IS NOT NULL AND coachID IS NOT NULL
[ "State", "the", "player", "ID", "and", "coach", "ID", "of", "person", "who", "have", "become", "coach", "after", "retirement", "." ]
[ { "id": 1, "type": "column", "value": "playerid" }, { "id": 2, "type": "column", "value": "coachid" }, { "id": 0, "type": "table", "value": "master" } ]
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1,621
department_store
spider:train_spider.json:4750
What is the id and name of the staff who has been assigned for the least amount of time?
SELECT T1.staff_id , T1.staff_name FROM staff AS T1 JOIN Staff_Department_Assignments AS T2 ON T1.staff_id = T2.staff_id ORDER BY date_assigned_to - date_assigned_from LIMIT 1
[ "What", "is", "the", "i", "d", "and", "name", "of", "the", "staff", "who", "has", "been", "assigned", "for", "the", "least", "amount", "of", "time", "?" ]
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1,622
railway
spider:train_spider.json:5636
What is the average age for all managers?
SELECT avg(Age) FROM manager
[ "What", "is", "the", "average", "age", "for", "all", "managers", "?" ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
1,623
car_road_race
bird:test.json:1316
List the winning drivers and winning teams of races in ascending alphabetical order of winning team.
SELECT Winning_driver , Winning_team FROM race ORDER BY Winning_team ASC
[ "List", "the", "winning", "drivers", "and", "winning", "teams", "of", "races", "in", "ascending", "alphabetical", "order", "of", "winning", "team", "." ]
[ { "id": 1, "type": "column", "value": "winning_driver" }, { "id": 2, "type": "column", "value": "winning_team" }, { "id": 0, "type": "table", "value": "race" } ]
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1,624
legislator
bird:train.json:4812
What is the gender of the legislator whose address at 317 Russell Senate Office Building Washington DC 20510?
SELECT T1.gender_bio FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T2.address = '317 Russell Senate Office Building Washington DC 20510'
[ "What", "is", "the", "gender", "of", "the", "legislator", "whose", "address", "at", "317", "Russell", "Senate", "Office", "Building", "Washington", "DC", "20510", "?" ]
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1,625
world_development_indicators
bird:train.json:2126
Which European countries had the highest private expenditure on health in 2005? List the top ten countries in descending order and find the source of the data.
SELECT DISTINCT T1.CountryCode, T3.Description FROM Country AS T1 INNER JOIN Indicators AS T2 ON T1.CountryCode = T2.CountryCode INNER JOIN CountryNotes AS T3 ON T1.CountryCode = T3.Countrycode WHERE T2.IndicatorName = 'Out-of-pocket health expenditure (% of private expenditure on health)' AND T2.Value > 0 AND T2.year ...
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1,626
loan_1
spider:train_spider.json:3011
What is the total number of customers who use banks in New York City?
SELECT sum(no_of_customers) FROM bank WHERE city = 'New York City'
[ "What", "is", "the", "total", "number", "of", "customers", "who", "use", "banks", "in", "New", "York", "City", "?" ]
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1,627
chicago_crime
bird:train.json:8651
Calculate the average crime rate per month in the highest populous area.
SELECT CAST(COUNT(T2.report_no) AS REAL) / 12 FROM Community_Area AS T1 INNER JOIN Crime AS T2 ON T2.community_area_no = T1.community_area_no GROUP BY T1.community_area_no HAVING COUNT(T1.population) ORDER BY COUNT(T1.population) LIMIT 1
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1,628
computer_student
bird:train.json:1011
Find the professor ID and position in faculty who taught high-level undergraduate course of less than 10 in ID.
SELECT T1.p_id, T1.hasPosition FROM person AS T1 INNER JOIN taughtBy AS T2 ON T1.p_id = T2.p_id INNER JOIN course AS T3 ON T3.course_id = T2.course_id WHERE T3.courseLevel = 'Level_400' AND T2.course_id < 10
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1,629
soccer_2
spider:train_spider.json:4948
How many colleges in total?
SELECT count(*) FROM College
[ "How", "many", "colleges", "in", "total", "?" ]
[ { "id": 0, "type": "table", "value": "college" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O" ]
1,630
music_tracker
bird:train.json:2088
Which artists have released singles with the tag 1970s?
SELECT T1.artist FROM torrents AS T1 INNER JOIN tags AS T2 ON T1.id = T2.id WHERE T1.releaseType = 'single' AND T2.tag LIKE '1970s'
[ "Which", "artists", "have", "released", "singles", "with", "the", "tag", "1970s", "?" ]
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1,632
computer_student
bird:train.json:981
Who are the professors who gave advice to students in the 12th years of program?
SELECT T1.p_id_dummy FROM advisedBy AS T1 INNER JOIN person AS T2 ON T1.p_id = T2.p_id WHERE T2.yearsInProgram = 'Year_12'
[ "Who", "are", "the", "professors", "who", "gave", "advice", "to", "students", "in", "the", "12th", "years", "of", "program", "?" ]
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1,633
retails
bird:train.json:6689
How many countries are there in the No.2 region?
SELECT COUNT(n_nationkey) FROM nation WHERE n_regionkey = 2
[ "How", "many", "countries", "are", "there", "in", "the", "No.2", "region", "?" ]
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1,634
department_store
spider:train_spider.json:4765
What are the phone numbers of all customers and suppliers.
SELECT customer_phone FROM customers UNION SELECT supplier_phone FROM suppliers
[ "What", "are", "the", "phone", "numbers", "of", "all", "customers", "and", "suppliers", "." ]
[ { "id": 2, "type": "column", "value": "customer_phone" }, { "id": 3, "type": "column", "value": "supplier_phone" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 1, "type": "table", "value": "suppliers" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-TABLE", "O" ]
1,635
small_bank_1
spider:train_spider.json:1812
Find the total checking and saving balance of all accounts sorted by the total balance in ascending order.
SELECT T1.balance + T2.balance FROM checking AS T1 JOIN savings AS T2 ON T1.custid = T2.custid ORDER BY T1.balance + T2.balance
[ "Find", "the", "total", "checking", "and", "saving", "balance", "of", "all", "accounts", "sorted", "by", "the", "total", "balance", "in", "ascending", "order", "." ]
[ { "id": 0, "type": "table", "value": "checking" }, { "id": 1, "type": "table", "value": "savings" }, { "id": 2, "type": "column", "value": "balance" }, { "id": 3, "type": "column", "value": "custid" } ]
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[ "O", "O", "O", "B-TABLE", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
1,636
legislator
bird:train.json:4834
List down the open secrets and thomas ID of the democrat senators of New Jersey.
SELECT T1.opensecrets_id, T1.thomas_id FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T2.type = 'sen' AND T2.state = 'NJ' GROUP BY T1.opensecrets_id, T1.thomas_id
[ "List", "down", "the", "open", "secrets", "and", "thomas", "ID", "of", "the", "democrat", "senators", "of", "New", "Jersey", "." ]
[ { "id": 0, "type": "column", "value": "opensecrets_id" }, { "id": 3, "type": "table", "value": "current-terms" }, { "id": 4, "type": "column", "value": "bioguide_id" }, { "id": 1, "type": "column", "value": "thomas_id" }, { "id": 5, "type": "co...
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O" ]
1,637
vehicle_driver
bird:test.json:176
Return the model and build year of cars that include "DJ" in their model names.
SELECT model , build_year FROM vehicle WHERE model LIKE '%DJ%'
[ "Return", "the", "model", "and", "build", "year", "of", "cars", "that", "include", "\"", "DJ", "\"", "in", "their", "model", "names", "." ]
[ { "id": 2, "type": "column", "value": "build_year" }, { "id": 0, "type": "table", "value": "vehicle" }, { "id": 1, "type": "column", "value": "model" }, { "id": 3, "type": "value", "value": "%DJ%" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "O" ]
1,639
insurance_fnol
spider:train_spider.json:892
What are all the phone numbers?
SELECT customer_phone FROM available_policies
[ "What", "are", "all", "the", "phone", "numbers", "?" ]
[ { "id": 0, "type": "table", "value": "available_policies" }, { "id": 1, "type": "column", "value": "customer_phone" } ]
[ { "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": [] ...
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O" ]
1,640
hockey
bird:train.json:7811
What is the total number of game played for players from USA?
SELECT COUNT(T2.GP) FROM Master AS T1 INNER JOIN Scoring AS T2 ON T1.playerID = T2.playerID WHERE T1.birthCountry = 'USA'
[ "What", "is", "the", "total", "number", "of", "game", "played", "for", "players", "from", "USA", "?" ]
[ { "id": 2, "type": "column", "value": "birthcountry" }, { "id": 5, "type": "column", "value": "playerid" }, { "id": 1, "type": "table", "value": "scoring" }, { "id": 0, "type": "table", "value": "master" }, { "id": 3, "type": "value", "valu...
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[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
1,641
law_episode
bird:train.json:1246
How many keywords are there for season 9, episode 23 of law_and_order?
SELECT COUNT(T2.keyword) FROM Episode AS T1 INNER JOIN Keyword AS T2 ON T1.episode_id = T2.episode_id WHERE T1.season = 9 AND T1.episode = 23
[ "How", "many", "keywords", "are", "there", "for", "season", "9", ",", "episode", "23", "of", "law_and_order", "?" ]
[ { "id": 3, "type": "column", "value": "episode_id" }, { "id": 0, "type": "table", "value": "episode" }, { "id": 1, "type": "table", "value": "keyword" }, { "id": 2, "type": "column", "value": "keyword" }, { "id": 6, "type": "column", "value...
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[ "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "B-VALUE", "O", "B-COLUMN", "B-VALUE", "O", "O", "O" ]
1,642
card_games
bird:dev.json:452
Please list the names of the cards that have a text box.
SELECT DISTINCT name FROM cards WHERE isTextless = 0
[ "Please", "list", "the", "names", "of", "the", "cards", "that", "have", "a", "text", "box", "." ]
[ { "id": 2, "type": "column", "value": "istextless" }, { "id": 0, "type": "table", "value": "cards" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "0" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
1,643
music_tracker
bird:train.json:2074
Which artist has released the most singles with the tag "soul"?
SELECT T1.artist FROM torrents AS T1 INNER JOIN tags AS T2 ON T1.id = T2.id WHERE T2.tag = 'soul' AND T1.releaseType = 'single' GROUP BY T1.artist ORDER BY COUNT(T1.releaseType) DESC LIMIT 1
[ "Which", "artist", "has", "released", "the", "most", "singles", "with", "the", "tag", "\"", "soul", "\"", "?" ]
[ { "id": 6, "type": "column", "value": "releasetype" }, { "id": 1, "type": "table", "value": "torrents" }, { "id": 0, "type": "column", "value": "artist" }, { "id": 7, "type": "value", "value": "single" }, { "id": 2, "type": "table", "value"...
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[ "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
1,644
chinook_1
spider:train_spider.json:881
What are the duration of the longest and shortest pop tracks in milliseconds?
SELECT max(Milliseconds) , min(Milliseconds) FROM GENRE AS T1 JOIN TRACK AS T2 ON T1.GenreId = T2.GenreId WHERE T1.Name = "Pop"
[ "What", "are", "the", "duration", "of", "the", "longest", "and", "shortest", "pop", "tracks", "in", "milliseconds", "?" ]
[ { "id": 4, "type": "column", "value": "milliseconds" }, { "id": 5, "type": "column", "value": "genreid" }, { "id": 0, "type": "table", "value": "genre" }, { "id": 1, "type": "table", "value": "track" }, { "id": 2, "type": "column", "value":...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, ...
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "O", "B-COLUMN", "O" ]
1,645
customers_and_invoices
spider:train_spider.json:1587
Show the transaction types and the total amount of transactions.
SELECT transaction_type , sum(transaction_amount) FROM Financial_transactions GROUP BY transaction_type
[ "Show", "the", "transaction", "types", "and", "the", "total", "amount", "of", "transactions", "." ]
[ { "id": 0, "type": "table", "value": "financial_transactions" }, { "id": 2, "type": "column", "value": "transaction_amount" }, { "id": 1, "type": "column", "value": "transaction_type" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
1,646
party_people
spider:train_spider.json:2041
Show all distinct region names ordered by their labels.
SELECT DISTINCT region_name FROM region ORDER BY Label
[ "Show", "all", "distinct", "region", "names", "ordered", "by", "their", "labels", "." ]
[ { "id": 1, "type": "column", "value": "region_name" }, { "id": 0, "type": "table", "value": "region" }, { "id": 2, "type": "column", "value": "label" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O" ]
1,647
cookbook
bird:train.json:8928
What ingredients does the longest cooking time recipe have?
SELECT T3.name FROM Recipe AS T1 INNER JOIN Quantity AS T2 ON T1.recipe_id = T2.recipe_id INNER JOIN Ingredient AS T3 ON T3.ingredient_id = T2.ingredient_id ORDER BY T1.cook_min DESC LIMIT 1
[ "What", "ingredients", "does", "the", "longest", "cooking", "time", "recipe", "have", "?" ]
[ { "id": 5, "type": "column", "value": "ingredient_id" }, { "id": 1, "type": "table", "value": "ingredient" }, { "id": 6, "type": "column", "value": "recipe_id" }, { "id": 2, "type": "column", "value": "cook_min" }, { "id": 4, "type": "table", ...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "...
[ "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O" ]
1,648
donor
bird:train.json:3290
What is the average total donations received by Fresno County colleges?
SELECT SUM(T2.donation_optional_support + T2.donation_to_project) / COUNT(donationid) FROM projects AS T1 INNER JOIN donations AS T2 ON T1.projectid = T2.projectid WHERE T1.school_county = 'Fresno'
[ "What", "is", "the", "average", "total", "donations", "received", "by", "Fresno", "County", "colleges", "?" ]
[ { "id": 6, "type": "column", "value": "donation_optional_support" }, { "id": 7, "type": "column", "value": "donation_to_project" }, { "id": 2, "type": "column", "value": "school_county" }, { "id": 5, "type": "column", "value": "donationid" }, { "id...
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[ "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "B-COLUMN", "O", "O" ]
1,649
cs_semester
bird:train.json:914
List the research assistants' full names, capabilities and GPAs who were under the supervision of Merwyn Conkay.
SELECT T3.f_name, T3.l_name, T2.capability, T3.gpa FROM prof AS T1 INNER JOIN RA AS T2 ON T1.prof_id = T2.prof_id INNER JOIN student AS T3 ON T2.student_id = T3.student_id WHERE T1.first_name = 'Merwyn' AND T1.last_name = 'Conkay'
[ "List", "the", "research", "assistants", "'", "full", "names", ",", "capabilities", "and", "GPAs", "who", "were", "under", "the", "supervision", "of", "Merwyn", "Conkay", "." ]
[ { "id": 2, "type": "column", "value": "capability" }, { "id": 7, "type": "column", "value": "student_id" }, { "id": 8, "type": "column", "value": "first_name" }, { "id": 10, "type": "column", "value": "last_name" }, { "id": 4, "type": "table", ...
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "B-VALUE", "B-VALUE", "O" ]
1,650
chicago_crime
bird:train.json:8687
Find the community area where the least number of domestic crimes happened.
SELECT T2.community_area_no FROM Crime AS T1 INNER JOIN Community_Area AS T2 ON T2.community_area_no = T1.community_area_no WHERE T1.domestic = 'TRUE' GROUP BY T2.community_area_no ORDER BY COUNT(T2.community_area_no) ASC LIMIT 1
[ "Find", "the", "community", "area", "where", "the", "least", "number", "of", "domestic", "crimes", "happened", "." ]
[ { "id": 0, "type": "column", "value": "community_area_no" }, { "id": 2, "type": "table", "value": "community_area" }, { "id": 3, "type": "column", "value": "domestic" }, { "id": 1, "type": "table", "value": "crime" }, { "id": 4, "type": "value"...
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[ "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "O", "O" ]
1,651
movie_3
bird:train.json:9248
How many customers rented for an above-average period?
SELECT COUNT(customer_id) FROM rental WHERE return_date - rental_date > ( SELECT AVG(return_date - rental_date) FROM rental )
[ "How", "many", "customers", "rented", "for", "an", "above", "-", "average", "period", "?" ]
[ { "id": 1, "type": "column", "value": "customer_id" }, { "id": 2, "type": "column", "value": "return_date" }, { "id": 3, "type": "column", "value": "rental_date" }, { "id": 0, "type": "table", "value": "rental" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": ...
[ "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "O", "O", "O", "O" ]
1,652
book_2
spider:train_spider.json:225
Show publishers that have more than one publication.
SELECT Publisher FROM publication GROUP BY Publisher HAVING COUNT(*) > 1
[ "Show", "publishers", "that", "have", "more", "than", "one", "publication", "." ]
[ { "id": 0, "type": "table", "value": "publication" }, { "id": 1, "type": "column", "value": "publisher" }, { "id": 2, "type": "value", "value": "1" } ]
[ { "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": ...
[ "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
1,653
retail_world
bird:train.json:6541
List down the customer company names, addresses, phones and faxes which are located in London.
SELECT CompanyName, Address, Phone, Fax FROM Customers WHERE City = 'London'
[ "List", "down", "the", "customer", "company", "names", ",", "addresses", ",", "phones", "and", "faxes", "which", "are", "located", "in", "London", "." ]
[ { "id": 1, "type": "column", "value": "companyname" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 2, "type": "column", "value": "address" }, { "id": 6, "type": "value", "value": "London" }, { "id": 3, "type": "column", "val...
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 4, 5 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [ 11 ...
[ "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O" ]
1,655
vehicle_driver
bird:test.json:178
Return the models of vehicles that have never been driven.
SELECT model FROM vehicle EXCEPT SELECT T1.model FROM vehicle AS T1 JOIN vehicle_driver AS T2 ON T1.vehicle_id = T2.vehicle_id
[ "Return", "the", "models", "of", "vehicles", "that", "have", "never", "been", "driven", "." ]
[ { "id": 2, "type": "table", "value": "vehicle_driver" }, { "id": 3, "type": "column", "value": "vehicle_id" }, { "id": 0, "type": "table", "value": "vehicle" }, { "id": 1, "type": "column", "value": "model" } ]
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[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
1,656
retail_world
bird:train.json:6647
List down the territory IDs, descriptions and region description which are under the in-charge of Nancy Davolio,
SELECT T3.RegionID, T3.TerritoryDescription, T4.RegionDescription FROM Employees AS T1 INNER JOIN EmployeeTerritories AS T2 ON T1.EmployeeID = T2.EmployeeID INNER JOIN Territories AS T3 ON T2.TerritoryID = T3.TerritoryID INNER JOIN Region AS T4 ON T3.RegionID = T4.RegionID WHERE T1.LastName = 'Davolio' AND T1.FirstName...
[ "List", "down", "the", "territory", "IDs", ",", "descriptions", "and", "region", "description", "which", "are", "under", "the", "in", "-", "charge", "of", "Nancy", "Davolio", "," ]
[ { "id": 1, "type": "column", "value": "territorydescription" }, { "id": 10, "type": "table", "value": "employeeterritories" }, { "id": 2, "type": "column", "value": "regiondescription" }, { "id": 4, "type": "table", "value": "territories" }, { "id"...
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-VALUE", "O" ]
1,657
e_commerce
bird:test.json:43
For every order, how many products does it contain, and what are the orders' statuses and ids?
SELECT T1.order_id , T1.order_status_code , count(*) FROM Orders AS T1 JOIN Order_items AS T2 ON T1.order_id = T2.order_id GROUP BY T1.order_id
[ "For", "every", "order", ",", "how", "many", "products", "does", "it", "contain", ",", "and", "what", "are", "the", "orders", "'", "statuses", "and", "ids", "?" ]
[ { "id": 1, "type": "column", "value": "order_status_code" }, { "id": 3, "type": "table", "value": "order_items" }, { "id": 0, "type": "column", "value": "order_id" }, { "id": 2, "type": "table", "value": "orders" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "O", "O" ]
1,658
mondial_geo
bird:train.json:8506
What percentage of countries became independent during the year 1960?
SELECT CAST(SUM(CASE WHEN STRFTIME('%Y', Independence) = '1960' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(Country) FROM politics
[ "What", "percentage", "of", "countries", "became", "independent", "during", "the", "year", "1960", "?" ]
[ { "id": 7, "type": "column", "value": "independence" }, { "id": 0, "type": "table", "value": "politics" }, { "id": 2, "type": "column", "value": "country" }, { "id": 5, "type": "value", "value": "1960" }, { "id": 1, "type": "value", "value"...
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[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
1,659
customer_complaints
spider:train_spider.json:5791
What are the prices of products that have never gotten a complaint?
SELECT product_price FROM products WHERE product_id NOT IN (SELECT product_id FROM complaints)
[ "What", "are", "the", "prices", "of", "products", "that", "have", "never", "gotten", "a", "complaint", "?" ]
[ { "id": 1, "type": "column", "value": "product_price" }, { "id": 2, "type": "column", "value": "product_id" }, { "id": 3, "type": "table", "value": "complaints" }, { "id": 0, "type": "table", "value": "products" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
1,660
chicago_crime
bird:train.json:8614
Who was the alderman of the legislative district where case No. JB103470 took place? Give the full name.
SELECT T1.alderman_first_name, T1.alderman_last_name FROM Ward AS T1 INNER JOIN Crime AS T2 ON T1.ward_no = T2.ward_no WHERE T2.case_number = 'JB103470'
[ "Who", "was", "the", "alderman", "of", "the", "legislative", "district", "where", "case", "No", ".", "JB103470", "took", "place", "?", "Give", "the", "full", "name", "." ]
[ { "id": 0, "type": "column", "value": "alderman_first_name" }, { "id": 1, "type": "column", "value": "alderman_last_name" }, { "id": 4, "type": "column", "value": "case_number" }, { "id": 5, "type": "value", "value": "JB103470" }, { "id": 6, "t...
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[ "O", "O", "O", "B-COLUMN", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O" ]
1,661
university_rank
bird:test.json:1768
What are the different home conferences from the university table?
SELECT DISTINCT home_conference FROM University
[ "What", "are", "the", "different", "home", "conferences", "from", "the", "university", "table", "?" ]
[ { "id": 1, "type": "column", "value": "home_conference" }, { "id": 0, "type": "table", "value": "university" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O" ]
1,662
cre_Students_Information_Systems
bird:test.json:458
What are the biographical data and the date of transcript issuance of each student?
SELECT T1.bio_data , T2.date_of_transcript FROM Students AS T1 JOIN Transcripts AS T2 ON T1.student_id = T2.student_id
[ "What", "are", "the", "biographical", "data", "and", "the", "date", "of", "transcript", "issuance", "of", "each", "student", "?" ]
[ { "id": 1, "type": "column", "value": "date_of_transcript" }, { "id": 3, "type": "table", "value": "transcripts" }, { "id": 4, "type": "column", "value": "student_id" }, { "id": 0, "type": "column", "value": "bio_data" }, { "id": 2, "type": "ta...
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "B-TABLE", "O", "O", "O", "B-TABLE", "O" ]
1,663
music_4
spider:train_spider.json:6161
Please list all songs in volumes in ascending alphabetical order.
SELECT Song FROM volume ORDER BY Song
[ "Please", "list", "all", "songs", "in", "volumes", "in", "ascending", "alphabetical", "order", "." ]
[ { "id": 0, "type": "table", "value": "volume" }, { "id": 1, "type": "column", "value": "song" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
1,664
soccer_3
bird:test.json:34
Show the country of players with earnings more than 1400000 and players with earnings less than 1100000.
SELECT Country FROM player WHERE Earnings > 1400000 INTERSECT SELECT Country FROM player WHERE Earnings < 1100000
[ "Show", "the", "country", "of", "players", "with", "earnings", "more", "than", "1400000", "and", "players", "with", "earnings", "less", "than", "1100000", "." ]
[ { "id": 2, "type": "column", "value": "earnings" }, { "id": 1, "type": "column", "value": "country" }, { "id": 3, "type": "value", "value": "1400000" }, { "id": 4, "type": "value", "value": "1100000" }, { "id": 0, "type": "table", "value": ...
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[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
1,665
video_games
bird:train.json:3387
Provide the ID of the most popular platform in Europe.
SELECT T.game_platform_id FROM ( SELECT T1.game_platform_id, SUM(T1.num_sales) FROM region_sales AS T1 INNER JOIN region AS T2 ON T1.region_id = T2.id WHERE T2.region_name = 'Europe' GROUP BY T1.game_platform_id ORDER BY SUM(T1.num_sales) DESC LIMIT 1 ) t
[ "Provide", "the", "ID", "of", "the", "most", "popular", "platform", "in", "Europe", "." ]
[ { "id": 0, "type": "column", "value": "game_platform_id" }, { "id": 1, "type": "table", "value": "region_sales" }, { "id": 3, "type": "column", "value": "region_name" }, { "id": 5, "type": "column", "value": "num_sales" }, { "id": 6, "type": "c...
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "O" ]
1,666
cre_Theme_park
spider:train_spider.json:5938
What are the average prices of hotels grouped by their pet policy.
SELECT pets_allowed_yn , avg(price_range) FROM HOTELS GROUP BY pets_allowed_yn
[ "What", "are", "the", "average", "prices", "of", "hotels", "grouped", "by", "their", "pet", "policy", "." ]
[ { "id": 1, "type": "column", "value": "pets_allowed_yn" }, { "id": 2, "type": "column", "value": "price_range" }, { "id": 0, "type": "table", "value": "hotels" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
1,667
retails
bird:train.json:6872
What is the total quantity available by all suppliers for the part "hot spring dodger dim light"?
SELECT SUM(T1.ps_availqty) FROM partsupp AS T1 INNER JOIN part AS T2 ON T1.ps_partkey = T2.p_partkey WHERE T2.p_name = 'hot spring dodger dim light'
[ "What", "is", "the", "total", "quantity", "available", "by", "all", "suppliers", "for", "the", "part", "\"", "hot", "spring", "dodger", "dim", "light", "\"", "?" ]
[ { "id": 3, "type": "value", "value": "hot spring dodger dim light" }, { "id": 4, "type": "column", "value": "ps_availqty" }, { "id": 5, "type": "column", "value": "ps_partkey" }, { "id": 6, "type": "column", "value": "p_partkey" }, { "id": 0, "...
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[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O" ]
1,668
network_2
spider:train_spider.json:4415
What is the age of the doctor named Zach?
SELECT age FROM Person WHERE job = 'doctor' AND name = 'Zach'
[ "What", "is", "the", "age", "of", "the", "doctor", "named", "Zach", "?" ]
[ { "id": 0, "type": "table", "value": "person" }, { "id": 3, "type": "value", "value": "doctor" }, { "id": 4, "type": "column", "value": "name" }, { "id": 5, "type": "value", "value": "Zach" }, { "id": 1, "type": "column", "value": "age" }...
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "B-COLUMN", "B-VALUE", "O" ]
1,669
superhero
bird:dev.json:787
What are the race and alignment of Cameron Hicks?
SELECT T2.race, T3.alignment FROM superhero AS T1 INNER JOIN race AS T2 ON T1.race_id = T2.id INNER JOIN alignment AS T3 ON T1.alignment_id = T3.id WHERE T1.superhero_name = 'Cameron Hicks'
[ "What", "are", "the", "race", "and", "alignment", "of", "Cameron", "Hicks", "?" ]
[ { "id": 3, "type": "column", "value": "superhero_name" }, { "id": 4, "type": "value", "value": "Cameron Hicks" }, { "id": 7, "type": "column", "value": "alignment_id" }, { "id": 1, "type": "column", "value": "alignment" }, { "id": 2, "type": "t...
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[ "O", "O", "O", "B-TABLE", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O" ]
1,670
hockey
bird:train.json:7626
State the nick name of player ID 'aubinje01'. List all the teams and season he played for.
SELECT DISTINCT T1.nameNick, T3.year, T3.name FROM Master AS T1 INNER JOIN Goalies AS T2 ON T1.playerID = T2.playerID INNER JOIN Teams AS T3 ON T2.tmID = T3.tmID WHERE T1.playerID = 'aubinje01'
[ "State", "the", "nick", "name", "of", "player", "ID", "'", "aubinje01", "'", ".", "List", "all", "the", "teams", "and", "season", "he", "played", "for", "." ]
[ { "id": 5, "type": "value", "value": "aubinje01" }, { "id": 0, "type": "column", "value": "namenick" }, { "id": 4, "type": "column", "value": "playerid" }, { "id": 7, "type": "table", "value": "goalies" }, { "id": 6, "type": "table", "value...
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[ "O", "O", "B-COLUMN", "B-COLUMN", "O", "B-COLUMN", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
1,671
public_review_platform
bird:train.json:3813
How many businesses in Scottsdale are rated as "wonderful experience"?
SELECT COUNT(business_id) FROM Business WHERE city LIKE 'Scottsdale' AND stars > 3
[ "How", "many", "businesses", "in", "Scottsdale", "are", "rated", "as", "\"", "wonderful", "experience", "\"", "?" ]
[ { "id": 1, "type": "column", "value": "business_id" }, { "id": 3, "type": "value", "value": "Scottsdale" }, { "id": 0, "type": "table", "value": "business" }, { "id": 4, "type": "column", "value": "stars" }, { "id": 2, "type": "column", "va...
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[ "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O" ]
1,672
social_media
bird:train.json:796
Give the number of users who do not show their genders.
SELECT COUNT(UserID) AS user_number FROM user WHERE Gender = 'Unknown'
[ "Give", "the", "number", "of", "users", "who", "do", "not", "show", "their", "genders", "." ]
[ { "id": 1, "type": "value", "value": "Unknown" }, { "id": 0, "type": "column", "value": "gender" }, { "id": 2, "type": "column", "value": "userid" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
1,673
formula_1
bird:dev.json:906
Which was Lewis Hamilton first race? What was his points recorded for his first race event?
SELECT T1.name, T2.points FROM races AS T1 INNER JOIN driverStandings AS T2 ON T2.raceId = T1.raceId INNER JOIN drivers AS T3 ON T3.driverId = T2.driverId WHERE T3.forename = 'Lewis' AND T3.surname = 'Hamilton' ORDER BY T1.year ASC LIMIT 1
[ "Which", "was", "Lewis", "Hamilton", "first", "race", "?", "What", "was", "his", "points", "recorded", "for", "his", "first", "race", "event", "?" ]
[ { "id": 5, "type": "table", "value": "driverstandings" }, { "id": 6, "type": "column", "value": "driverid" }, { "id": 7, "type": "column", "value": "forename" }, { "id": 10, "type": "value", "value": "Hamilton" }, { "id": 2, "type": "table", ...
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[ "O", "O", "B-VALUE", "B-VALUE", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
1,675
books
bird:train.json:5928
Which city does the address id 547 belong to?
SELECT city FROM address WHERE address_id = 547
[ "Which", "city", "does", "the", "address", "i", "d", "547", "belong", "to", "?" ]
[ { "id": 2, "type": "column", "value": "address_id" }, { "id": 0, "type": "table", "value": "address" }, { "id": 1, "type": "column", "value": "city" }, { "id": 3, "type": "value", "value": "547" } ]
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[ "O", "B-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "B-VALUE", "O", "O", "O" ]
1,676
regional_sales
bird:train.json:2619
List out the discount levels applied for all orders from Ole Group.
SELECT T FROM ( SELECT DISTINCT CASE WHEN T1.`Customer Names` = 'Ole Group' THEN T2.`Discount Applied` END AS T FROM Customers T1 INNER JOIN `Sales Orders` T2 ON T2._CustomerID = T1.CustomerID ) WHERE T IS NOT NULL
[ "List", "out", "the", "discount", "levels", "applied", "for", "all", "orders", "from", "Ole", "Group", "." ]
[ { "id": 5, "type": "column", "value": "Discount Applied" }, { "id": 6, "type": "column", "value": "Customer Names" }, { "id": 2, "type": "table", "value": "Sales Orders" }, { "id": 3, "type": "column", "value": "_customerid" }, { "id": 4, "type...
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-TABLE", "I-TABLE", "O", "B-VALUE", "I-VALUE", "O" ]
1,677
college_2
spider:train_spider.json:1359
What are the names and budgets of departments with budgets greater than the average?
SELECT dept_name , budget FROM department WHERE budget > (SELECT avg(budget) FROM department)
[ "What", "are", "the", "names", "and", "budgets", "of", "departments", "with", "budgets", "greater", "than", "the", "average", "?" ]
[ { "id": 0, "type": "table", "value": "department" }, { "id": 1, "type": "column", "value": "dept_name" }, { "id": 2, "type": "column", "value": "budget" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
1,678
movie_3
bird:train.json:9393
Provide the full name of all the actors of the film "Ending Crowds".
SELECT T2.first_name, T2.last_name FROM film_actor AS T1 INNER JOIN actor AS T2 ON T1.actor_id = T2.actor_id INNER JOIN film AS T3 ON T1.film_id = T3.film_id WHERE T3.title = 'ENDING CROWDS'
[ "Provide", "the", "full", "name", "of", "all", "the", "actors", "of", "the", "film", "\"", "Ending", "Crowds", "\"", "." ]
[ { "id": 4, "type": "value", "value": "ENDING CROWDS" }, { "id": 0, "type": "column", "value": "first_name" }, { "id": 5, "type": "table", "value": "film_actor" }, { "id": 1, "type": "column", "value": "last_name" }, { "id": 8, "type": "column",...
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O", "O" ]
1,680
european_football_2
bird:dev.json:1141
Does the KSV Cercle Brugge team have a slow, balanced or fast speed class?
SELECT DISTINCT t1.buildUpPlaySpeedClass FROM Team_Attributes AS t1 INNER JOIN Team AS t2 ON t1.team_api_id = t2.team_api_id WHERE t2.team_long_name = 'KSV Cercle Brugge'
[ "Does", "the", "KSV", "Cercle", "Brugge", "team", "have", "a", "slow", ",", "balanced", "or", "fast", "speed", "class", "?" ]
[ { "id": 0, "type": "column", "value": "buildupplayspeedclass" }, { "id": 4, "type": "value", "value": "KSV Cercle Brugge" }, { "id": 1, "type": "table", "value": "team_attributes" }, { "id": 3, "type": "column", "value": "team_long_name" }, { "id":...
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[ "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
1,681
formula_1
spider:train_spider.json:2175
Give me a list of names and years of races that had any driver whose forename is Lewis?
SELECT T2.name , T2.year FROM results AS T1 JOIN races AS T2 ON T1.raceid = T2.raceid JOIN drivers AS T3 ON T1.driverid = T3.driverid WHERE T3.forename = "Lewis"
[ "Give", "me", "a", "list", "of", "names", "and", "years", "of", "races", "that", "had", "any", "driver", "whose", "forename", "is", "Lewis", "?" ]
[ { "id": 3, "type": "column", "value": "forename" }, { "id": 7, "type": "column", "value": "driverid" }, { "id": 2, "type": "table", "value": "drivers" }, { "id": 5, "type": "table", "value": "results" }, { "id": 8, "type": "column", "value"...
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 13 ] }, { "entity_id": 3, "token_idxs": [ 15 ] }, { "entity_id": 4, "token_idxs": [ 17 ] }, ...
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "B-COLUMN", "O" ]
1,682
beer_factory
bird:train.json:5309
What brands of beer has Peg Winchester consumed?
SELECT T3.BrandName FROM customers AS T1 INNER JOIN rootbeerreview AS T2 ON T1.CustomerID = T2.CustomerID INNER JOIN rootbeerbrand AS T3 ON T2.BrandID = T3.BrandID WHERE T1.First = 'Peg' AND T1.Last = 'Winchester'
[ "What", "brands", "of", "beer", "has", "Peg", "Winchester", "consumed", "?" ]
[ { "id": 3, "type": "table", "value": "rootbeerreview" }, { "id": 1, "type": "table", "value": "rootbeerbrand" }, { "id": 8, "type": "value", "value": "Winchester" }, { "id": 9, "type": "column", "value": "customerid" }, { "id": 0, "type": "colu...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 1 ] }, { "entity_id": 5, "token_idxs": [] }, { ...
[ "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "B-VALUE", "O", "O" ]
1,683
talkingdata
bird:train.json:1122
Give the time stamp for event No.887711.
SELECT timestamp FROM events WHERE event_id = '887711'
[ "Give", "the", "time", "stamp", "for", "event", "No.887711", "." ]
[ { "id": 1, "type": "column", "value": "timestamp" }, { "id": 2, "type": "column", "value": "event_id" }, { "id": 0, "type": "table", "value": "events" }, { "id": 3, "type": "value", "value": "887711" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "B-VALUE", "O" ]
1,685
movie_platform
bird:train.json:84
Who was the director of the movie "Tokyo Eyes"?
SELECT director_name FROM movies WHERE movie_title = 'Tokyo Eyes'
[ "Who", "was", "the", "director", "of", "the", "movie", "\"", "Tokyo", "Eyes", "\"", "?" ]
[ { "id": 1, "type": "column", "value": "director_name" }, { "id": 2, "type": "column", "value": "movie_title" }, { "id": 3, "type": "value", "value": "Tokyo Eyes" }, { "id": 0, "type": "table", "value": "movies" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8, 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id":...
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O", "O" ]
1,686
allergy_1
spider:train_spider.json:482
Give the number of students living in either HKG or CHI.
SELECT count(*) FROM Student WHERE city_code = "HKG" OR city_code = "CHI"
[ "Give", "the", "number", "of", "students", "living", "in", "either", "HKG", "or", "CHI", "." ]
[ { "id": 1, "type": "column", "value": "city_code" }, { "id": 0, "type": "table", "value": "student" }, { "id": 2, "type": "column", "value": "HKG" }, { "id": 3, "type": "column", "value": "CHI" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, ...
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O" ]
1,687
cre_Docs_and_Epenses
spider:train_spider.json:6435
What is the project id and detail for the project with at least two documents?
SELECT T1.project_id , T1.project_details FROM Projects AS T1 JOIN Documents AS T2 ON T1.project_id = T2.project_id GROUP BY T1.project_id HAVING count(*) > 2
[ "What", "is", "the", "project", "i", "d", "and", "detail", "for", "the", "project", "with", "at", "least", "two", "documents", "?" ]
[ { "id": 1, "type": "column", "value": "project_details" }, { "id": 0, "type": "column", "value": "project_id" }, { "id": 3, "type": "table", "value": "documents" }, { "id": 2, "type": "table", "value": "projects" }, { "id": 4, "type": "value", ...
[ { "entity_id": 0, "token_idxs": [ 3, 4, 5 ] }, { "entity_id": 1, "token_idxs": [ 6, 7 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 15 ] }, { "entity_id": 4, "token_id...
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O" ]
1,688
election
spider:train_spider.json:2746
Show the delegate from district 1 in election.
SELECT Delegate FROM election WHERE District = 1
[ "Show", "the", "delegate", "from", "district", "1", "in", "election", "." ]
[ { "id": 0, "type": "table", "value": "election" }, { "id": 1, "type": "column", "value": "delegate" }, { "id": 2, "type": "column", "value": "district" }, { "id": 3, "type": "value", "value": "1" } ]
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[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "B-VALUE", "O", "B-TABLE", "O" ]
1,689
student_assessment
spider:train_spider.json:77
What is detail of the student who registered the most number of courses?
SELECT T1.student_details FROM students AS T1 JOIN student_course_registrations AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1
[ "What", "is", "detail", "of", "the", "student", "who", "registered", "the", "most", "number", "of", "courses", "?" ]
[ { "id": 3, "type": "table", "value": "student_course_registrations" }, { "id": 1, "type": "column", "value": "student_details" }, { "id": 0, "type": "column", "value": "student_id" }, { "id": 2, "type": "table", "value": "students" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "B-TABLE", "I-TABLE", "I-TABLE", "I-TABLE", "O", "O", "O", "O" ]
1,690
cars
bird:train.json:3099
Among the cars with an engine displacement of no less than 400 cubic millimeter, how many cars cost at least 30,000?
SELECT COUNT(*) FROM data AS T1 INNER JOIN price AS T2 ON T1.ID = T2.ID WHERE T1.displacement > 400 AND T2.price > 30000
[ "Among", "the", "cars", "with", "an", "engine", "displacement", "of", "no", "less", "than", "400", "cubic", "millimeter", ",", "how", "many", "cars", "cost", "at", "least", "30,000", "?" ]
[ { "id": 3, "type": "column", "value": "displacement" }, { "id": 1, "type": "table", "value": "price" }, { "id": 5, "type": "column", "value": "price" }, { "id": 6, "type": "value", "value": "30000" }, { "id": 0, "type": "table", "value": "d...
[ { "entity_id": 0, "token_idxs": [ 19 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, ...
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O" ]
1,691
movie_3
bird:train.json:9199
Who are the top 5 actors with the highest number of films? List their full names and calculate the average number of films for each of the actors.
SELECT T.first_name, T.last_name, num FROM ( SELECT T1.first_name, T1.last_name, COUNT(T2.film_id) AS num FROM actor AS T1 INNER JOIN film_actor AS T2 ON T1.actor_id = T2.actor_id INNER JOIN film AS T3 ON T2.film_id = T3.film_id GROUP BY T1.first_name, T1.last_name ) AS T ORDER BY T.num DESC LIMIT 5
[ "Who", "are", "the", "top", "5", "actors", "with", "the", "highest", "number", "of", "films", "?", "List", "their", "full", "names", "and", "calculate", "the", "average", "number", "of", "films", "for", "each", "of", "the", "actors", "." ]
[ { "id": 0, "type": "column", "value": "first_name" }, { "id": 6, "type": "table", "value": "film_actor" }, { "id": 1, "type": "column", "value": "last_name" }, { "id": 7, "type": "column", "value": "actor_id" }, { "id": 4, "type": "column", ...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 21 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs"...
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "O", "O" ]
1,692
allergy_1
spider:train_spider.json:439
How many allergies are there?
SELECT count(DISTINCT allergy) FROM Allergy_type
[ "How", "many", "allergies", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "allergy_type" }, { "id": 1, "type": "column", "value": "allergy" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { ...
[ "O", "O", "B-COLUMN", "O", "O", "O" ]
1,693
loan_1
spider:train_spider.json:3050
Find the name, account type, and account balance of the customer who has the highest credit score.
SELECT cust_name , acc_type , acc_bal FROM customer ORDER BY credit_score DESC LIMIT 1
[ "Find", "the", "name", ",", "account", "type", ",", "and", "account", "balance", "of", "the", "customer", "who", "has", "the", "highest", "credit", "score", "." ]
[ { "id": 4, "type": "column", "value": "credit_score" }, { "id": 1, "type": "column", "value": "cust_name" }, { "id": 0, "type": "table", "value": "customer" }, { "id": 2, "type": "column", "value": "acc_type" }, { "id": 3, "type": "column", ...
[ { "entity_id": 0, "token_idxs": [ 12 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 4, 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 17, 18 ] }, { ...
[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
1,694
small_bank_1
spider:train_spider.json:1791
What are the checking and savings balances in accounts belonging to Brown?
SELECT T2.balance , T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T1.name = 'Brown'
[ "What", "are", "the", "checking", "and", "savings", "balances", "in", "accounts", "belonging", "to", "Brown", "?" ]
[ { "id": 4, "type": "table", "value": "accounts" }, { "id": 5, "type": "table", "value": "checking" }, { "id": 0, "type": "column", "value": "balance" }, { "id": 1, "type": "table", "value": "savings" }, { "id": 6, "type": "column", "value":...
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [ 8 ] }, { "entity...
[ "O", "O", "O", "B-TABLE", "O", "B-TABLE", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-VALUE", "O" ]
1,695
student_club
bird:dev.json:1406
Among the budgets for Food, which one has the highest budgeted amount?
SELECT budget_id FROM budget WHERE category = 'Food' AND amount = ( SELECT MAX(amount) FROM budget )
[ "Among", "the", "budgets", "for", "Food", ",", "which", "one", "has", "the", "highest", "budgeted", "amount", "?" ]
[ { "id": 1, "type": "column", "value": "budget_id" }, { "id": 2, "type": "column", "value": "category" }, { "id": 0, "type": "table", "value": "budget" }, { "id": 4, "type": "column", "value": "amount" }, { "id": 3, "type": "value", "value":...
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entit...
[ "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O" ]
1,696
government_shift
bird:test.json:367
Find the name of the customer who has used the most types of services .
select t1.customer_details from customers as t1 join customers_and_services as t2 on t1.customer_id = t2.customer_id group by t1.customer_details order by count(*) desc limit 1
[ "Find", "the", "name", "of", "the", "customer", "who", "has", "used", "the", "most", "types", "of", "services", "." ]
[ { "id": 2, "type": "table", "value": "customers_and_services" }, { "id": 0, "type": "column", "value": "customer_details" }, { "id": 3, "type": "column", "value": "customer_id" }, { "id": 1, "type": "table", "value": "customers" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { ...
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
1,698
college_2
spider:train_spider.json:1348
Find the name of the courses that do not have any prerequisite?
SELECT title FROM course WHERE course_id NOT IN (SELECT course_id FROM prereq)
[ "Find", "the", "name", "of", "the", "courses", "that", "do", "not", "have", "any", "prerequisite", "?" ]
[ { "id": 2, "type": "column", "value": "course_id" }, { "id": 0, "type": "table", "value": "course" }, { "id": 3, "type": "table", "value": "prereq" }, { "id": 1, "type": "column", "value": "title" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs":...
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
1,699
formula_1
bird:dev.json:897
Name the driver with the most winning. Mention his nationality and what is his maximum point scores.
SELECT T1.forename, T1.surname, T1.nationality, MAX(T2.points) FROM drivers AS T1 INNER JOIN driverStandings AS T2 ON T2.driverId = T1.driverId WHERE T2.wins >= 1 GROUP BY T1.forename, T1.surname, T1.nationality ORDER BY COUNT(T2.wins) DESC LIMIT 1
[ "Name", "the", "driver", "with", "the", "most", "winning", ".", "Mention", "his", "nationality", "and", "what", "is", "his", "maximum", "point", "scores", "." ]
[ { "id": 4, "type": "table", "value": "driverstandings" }, { "id": 2, "type": "column", "value": "nationality" }, { "id": 0, "type": "column", "value": "forename" }, { "id": 8, "type": "column", "value": "driverid" }, { "id": 1, "type": "column"...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 0 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, ...
[ "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O" ]
1,700
music_4
spider:train_spider.json:6193
What are the date of ceremony of music festivals with category "Best Song" and result "Awarded"?
SELECT Date_of_ceremony FROM music_festival WHERE Category = "Best Song" AND RESULT = "Awarded"
[ "What", "are", "the", "date", "of", "ceremony", "of", "music", "festivals", "with", "category", "\"", "Best", "Song", "\"", "and", "result", "\"", "Awarded", "\"", "?" ]
[ { "id": 1, "type": "column", "value": "date_of_ceremony" }, { "id": 0, "type": "table", "value": "music_festival" }, { "id": 3, "type": "column", "value": "Best Song" }, { "id": 2, "type": "column", "value": "category" }, { "id": 5, "type": "co...
[ { "entity_id": 0, "token_idxs": [ 7, 8 ] }, { "entity_id": 1, "token_idxs": [ 3, 4, 5 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 12, 13 ] }, { "entity_id": 4, ...
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-TABLE", "I-TABLE", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O" ]
1,701
works_cycles
bird:train.json:7138
What percentage of AdventureWorks employees are men?
SELECT CAST(SUM(CASE WHEN T2.Gender = 'M' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.BusinessentityID) FROM Person AS T1 INNER JOIN Employee AS T2 ON T1.BusinessentityID = T2.BusinessentityID WHERE T1.PersonType = 'EM'
[ "What", "percentage", "of", "AdventureWorks", "employees", "are", "men", "?" ]
[ { "id": 4, "type": "column", "value": "businessentityid" }, { "id": 2, "type": "column", "value": "persontype" }, { "id": 1, "type": "table", "value": "employee" }, { "id": 0, "type": "table", "value": "person" }, { "id": 8, "type": "column", ...
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [ 1 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": ...
[ "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O" ]
1,702
advertising_agencies
bird:test.json:2061
Show the number of clients.
SELECT count(*) FROM Clients
[ "Show", "the", "number", "of", "clients", "." ]
[ { "id": 0, "type": "table", "value": "clients" } ]
[ { "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": [] }, { ...
[ "O", "O", "O", "O", "B-TABLE", "O" ]
1,703
inn_1
spider:train_spider.json:2584
How many adults stay in the room CONRAD SELBIG checked in on Oct 23, 2010?
SELECT Adults FROM Reservations WHERE CheckIn = "2010-10-23" AND FirstName = "CONRAD" AND LastName = "SELBIG";
[ "How", "many", "adults", "stay", "in", "the", "room", "CONRAD", "SELBIG", "checked", "in", "on", "Oct", "23", ",", "2010", "?" ]
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1,704
ice_hockey_draft
bird:train.json:6932
What is the height in centimeter of the tallest player born in Edmonton, Alberta, Canada?
SELECT T2.height_in_cm FROM PlayerInfo AS T1 INNER JOIN height_info AS T2 ON T1.height = T2.height_id WHERE T1.birthplace = 'Edmonton, AB, CAN' ORDER BY T2.height_in_cm DESC LIMIT 1
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1,705
address
bird:train.json:5118
How many counties are there in Virginia State?
SELECT COUNT(T2.county) FROM state AS T1 INNER JOIN country AS T2 ON T1.abbreviation = T2.state WHERE T1.name = 'Virginia'
[ "How", "many", "counties", "are", "there", "in", "Virginia", "State", "?" ]
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1,706
world_development_indicators
bird:train.json:2231
What's the lastest household survey in Angola and when did it take place?
SELECT LatestHouseholdSurvey, PppSurveyYear FROM Country WHERE ShortName = 'Angola'
[ "What", "'s", "the", "lastest", "household", "survey", "in", "Angola", "and", "when", "did", "it", "take", "place", "?" ]
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1,707
election
spider:train_spider.json:2734
How many counties are there in total?
SELECT count(*) FROM county
[ "How", "many", "counties", "are", "there", "in", "total", "?" ]
[ { "id": 0, "type": "table", "value": "county" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
1,708
shakespeare
bird:train.json:3053
Who is the character that said "This is Illyria, lady."?
SELECT T1.CharName FROM characters AS T1 INNER JOIN paragraphs AS T2 ON T1.id = T2.character_id WHERE T2.PlainText = 'This is Illyria, lady.'
[ "Who", "is", "the", "character", "that", "said", "\"", "This", "is", "Illyria", ",", "lady", ".", "\"", "?" ]
[ { "id": 4, "type": "value", "value": "This is Illyria, lady." }, { "id": 6, "type": "column", "value": "character_id" }, { "id": 1, "type": "table", "value": "characters" }, { "id": 2, "type": "table", "value": "paragraphs" }, { "id": 3, "type"...
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1,709
card_games
bird:dev.json:413
How many cards with print rarity have ruling text printed on 01/02/2007?
SELECT COUNT(DISTINCT T1.id) FROM cards AS T1 INNER JOIN rulings AS T2 ON T1.uuid = T2.uuid WHERE T1.rarity = 'rare' AND T2.date = '2007-02-01'
[ "How", "many", "cards", "with", "print", "rarity", "have", "ruling", "text", "printed", "on", "01/02/2007", "?" ]
[ { "id": 7, "type": "value", "value": "2007-02-01" }, { "id": 1, "type": "table", "value": "rulings" }, { "id": 4, "type": "column", "value": "rarity" }, { "id": 0, "type": "table", "value": "cards" }, { "id": 3, "type": "column", "value": "...
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[ "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
1,710
food_inspection_2
bird:train.json:6244
How many of the inspections with serious point levels have no fines?
SELECT COUNT(DISTINCT T2.inspection_id) FROM inspection_point AS T1 INNER JOIN violation AS T2 ON T1.point_id = T2.point_id WHERE T1.point_level = 'Serious ' AND T2.fine = 0
[ "How", "many", "of", "the", "inspections", "with", "serious", "point", "levels", "have", "no", "fines", "?" ]
[ { "id": 0, "type": "table", "value": "inspection_point" }, { "id": 2, "type": "column", "value": "inspection_id" }, { "id": 4, "type": "column", "value": "point_level" }, { "id": 1, "type": "table", "value": "violation" }, { "id": 3, "type": "c...
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1,711
ice_hockey_draft
bird:train.json:6930
How many right-shooted players have a height of 5'7''?
SELECT COUNT(T1.ELITEID) FROM PlayerInfo AS T1 INNER JOIN height_info AS T2 ON T1.height = T2.height_id WHERE T2.height_in_inch = '5''7"' AND T1.shoots = 'R'
[ "How", "many", "right", "-", "shooted", "players", "have", "a", "height", "of", "5'7", "''", "?" ]
[ { "id": 5, "type": "column", "value": "height_in_inch" }, { "id": 1, "type": "table", "value": "height_info" }, { "id": 0, "type": "table", "value": "playerinfo" }, { "id": 4, "type": "column", "value": "height_id" }, { "id": 2, "type": "column...
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[ "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
1,712
sales_in_weather
bird:train.json:8165
For the home weather station of store no.15, what was the dew point on 2012/2/18?
SELECT T1.dewpoint FROM weather AS T1 INNER JOIN relation AS T2 ON T1.station_nbr = T2.station_nbr WHERE T2.store_nbr = 15 AND T1.`date` = '2012-02-18'
[ "For", "the", "home", "weather", "station", "of", "store", "no.15", ",", "what", "was", "the", "dew", "point", "on", "2012/2/18", "?" ]
[ { "id": 3, "type": "column", "value": "station_nbr" }, { "id": 7, "type": "value", "value": "2012-02-18" }, { "id": 4, "type": "column", "value": "store_nbr" }, { "id": 0, "type": "column", "value": "dewpoint" }, { "id": 2, "type": "table", ...
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1,713
college_1
spider:train_spider.json:3197
Find the number of different departments in each school whose number of different departments is less than 5.
SELECT count(DISTINCT dept_name) , school_code FROM department GROUP BY school_code HAVING count(DISTINCT dept_name) < 5
[ "Find", "the", "number", "of", "different", "departments", "in", "each", "school", "whose", "number", "of", "different", "departments", "is", "less", "than", "5", "." ]
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1,714
car_retails
bird:train.json:1592
What is the total value of shipped vintage car orders from 2003-2004?
SELECT SUM(T2.priceEach * T2.quantityOrdered) FROM products AS T1 INNER JOIN orderdetails AS T2 ON T1.productCode = T2.productCode INNER JOIN orders AS T3 ON T2.orderNumber = T3.orderNumber WHERE T3.status = 'Shipped' AND T3.orderDate BETWEEN '2003-01-01' AND '2004-12-31'
[ "What", "is", "the", "total", "value", "of", "shipped", "vintage", "car", "orders", "from", "2003", "-", "2004", "?" ]
[ { "id": 10, "type": "column", "value": "quantityordered" }, { "id": 2, "type": "table", "value": "orderdetails" }, { "id": 3, "type": "column", "value": "ordernumber" }, { "id": 11, "type": "column", "value": "productcode" }, { "id": 7, "type":...
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1,715
legislator
bird:train.json:4850
How many legislators are not senator?
SELECT COUNT(bioguide) FROM `current-terms` WHERE class IS NULL
[ "How", "many", "legislators", "are", "not", "senator", "?" ]
[ { "id": 0, "type": "table", "value": "current-terms" }, { "id": 2, "type": "column", "value": "bioguide" }, { "id": 1, "type": "column", "value": "class" } ]
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[ "O", "O", "O", "O", "O", "O", "O" ]
1,716
airline
bird:train.json:5863
Among the airports whose destination is Logan International, what is the airline id of the carrier operator with the highest delay in minutes due to security?
SELECT T2.OP_CARRIER_AIRLINE_ID FROM Airports AS T1 INNER JOIN Airlines AS T2 ON T1.Code = T2.DEST WHERE T1.Description = 'Boston, MA: Logan International' AND T2.DEST = 'BOS' ORDER BY T2.SECURITY_DELAY DESC LIMIT 1
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[ { "id": 7, "type": "value", "value": "Boston, MA: Logan International" }, { "id": 0, "type": "column", "value": "op_carrier_airline_id" }, { "id": 3, "type": "column", "value": "security_delay" }, { "id": 6, "type": "column", "value": "description" }, ...
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1,717
pilot_1
bird:test.json:1146
What are the names of pilots who own both Piper Cub and the B-52 Bomber?
SELECT pilot_name FROM pilotskills WHERE plane_name = 'Piper Cub' INTERSECT SELECT pilot_name FROM pilotskills WHERE plane_name = 'B-52 Bomber'
[ "What", "are", "the", "names", "of", "pilots", "who", "own", "both", "Piper", "Cub", "and", "the", "B-52", "Bomber", "?" ]
[ { "id": 0, "type": "table", "value": "pilotskills" }, { "id": 4, "type": "value", "value": "B-52 Bomber" }, { "id": 1, "type": "column", "value": "pilot_name" }, { "id": 2, "type": "column", "value": "plane_name" }, { "id": 3, "type": "value", ...
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[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "B-VALUE", "I-VALUE", "O" ]
1,718
manufactory_1
spider:train_spider.json:5303
What are the names of companies with revenue less than the lowest revenue of any manufacturer in Austin?
SELECT name FROM manufacturers WHERE revenue < (SELECT min(revenue) FROM manufacturers WHERE headquarter = 'Austin')
[ "What", "are", "the", "names", "of", "companies", "with", "revenue", "less", "than", "the", "lowest", "revenue", "of", "any", "manufacturer", "in", "Austin", "?" ]
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