question_id int64 0 16.1k | db_id stringclasses 259
values | dber_id stringlengths 15 29 | question stringlengths 16 325 | SQL stringlengths 18 1.25k | tokens listlengths 4 62 | entities listlengths 0 21 | entity_to_token listlengths 20 20 | dber_tags listlengths 4 62 |
|---|---|---|---|---|---|---|---|---|
11,879 | soccer_2016 | bird:train.json:1996 | What is the venue for the match ID 829768? | SELECT T1.Venue_Name FROM Venue AS T1 INNER JOIN Match AS T2 ON T1.venue_id = T2.venue_id WHERE T2.match_id = 829768 | [
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11,880 | cs_semester | bird:train.json:910 | What is the male and female ratio among the professors? | SELECT CAST(SUM(CASE WHEN gender = 'Male' THEN 1 ELSE 0 END) AS REAL) / SUM(CASE WHEN gender = 'Female' THEN 1 ELSE 0 END) FROM prof | [
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11,881 | public_review_platform | bird:train.json:3968 | How many times is the number of "Women's Clothing" Yelp businesses to "Men's Clothing"? | SELECT CAST(SUM(CASE WHEN T2.category_name = 'Women''s Clothing' THEN 1 ELSE 0 END) AS REAL) / SUM(CASE WHEN T2.category_name = 'Men''s Clothing' THEN 1 ELSE 0 END) AS TIMES FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id | [
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11,882 | dorm_1 | spider:train_spider.json:5757 | What are the first names of all students who live in the dorm with the most amenities? | SELECT T1.fname FROM student AS T1 JOIN lives_in AS T2 ON T1.stuid = T2.stuid WHERE T2.dormid IN (SELECT T2.dormid FROM dorm AS T3 JOIN has_amenity AS T4 ON T3.dormid = T4.dormid JOIN dorm_amenity AS T5 ON T4.amenid = T5.amenid GROUP BY T3.dormid ORDER BY count(*) DESC LIMIT 1) | [
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11,883 | shakespeare | bird:train.json:2979 | Which Shakespeare story with character ID 324 has description of 'this friend of Caesar'? | SELECT T1.Title FROM works AS T1 INNER JOIN chapters AS T2 ON T1.id = T2.work_id INNER JOIN paragraphs AS T3 ON T2.id = T3.chapter_id INNER JOIN characters AS T4 ON T3.character_id = T4.id WHERE T2.id = '324' AND T2.Description = 'friend to Caesar' | [
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11,884 | superhero | bird:dev.json:737 | What is Copycat's race? | SELECT T2.race FROM superhero AS T1 INNER JOIN race AS T2 ON T1.race_id = T2.id WHERE T1.superhero_name = 'Copycat' | [
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11,885 | retail_complains | bird:train.json:336 | List all the issues of the complaints made by Kaitlyn Eliza Elliott. | SELECT DISTINCT T2.Issue FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.first = 'Kaitlyn' AND T1.middle = 'Eliza' AND T1.last = 'Elliott' | [
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11,886 | debit_card_specializing | bird:dev.json:1528 | What is the percentage of "premium" against the overall segment in Country = "SVK"? | SELECT CAST(SUM(IIF(Country = 'SVK' AND Segment = 'Premium', 1, 0)) AS FLOAT) * 100 / SUM(IIF(Country = 'SVK', 1, 0)) FROM gasstations | [
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11,887 | app_store | bird:train.json:2547 | What is the rating and the total Sentiment subjectivity score of "Onefootball - Soccer Scores"? | SELECT T1.Rating, SUM(T2.Sentiment_Subjectivity) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Onefootball - Soccer Scores' | [
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11,888 | cre_Students_Information_Systems | bird:test.json:489 | What is the least common detention type? Show the type code and the description. | SELECT T1.detention_type_code , T2.detention_type_description FROM Detention AS T1 JOIN Ref_Detention_Type AS T2 ON T1.detention_type_code = T2.detention_type_code GROUP BY T1.detention_type_code ORDER BY count(*) ASC LIMIT 1 | [
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11,889 | workshop_paper | spider:train_spider.json:5835 | Which submission received the highest score in acceptance result. Show me the result. | SELECT T1.Result FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID ORDER BY T2.Scores DESC LIMIT 1 | [
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11,890 | shakespeare | bird:train.json:2985 | How many "servant to Timon" characters are there? | SELECT COUNT(id) FROM characters WHERE Description = 'servant to Timon' | [
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11,891 | student_club | bird:dev.json:1450 | In the events with more than forty incomes, list the city and country in which the event is happening. | SELECT DISTINCT T3.city, T3.county FROM income AS T1 INNER JOIN member AS T2 ON T1.link_to_member = T2.member_id INNER JOIN zip_code AS T3 ON T3.zip_code = T2.zip WHERE T1.amount > 40 | [
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11,892 | mental_health_survey | bird:train.json:4620 | List the top three popular responses to the question of the survey in 2017 with the question ID no.85. | SELECT AnswerText FROM Answer WHERE QuestionID = 85 AND SurveyID = 2017 GROUP BY AnswerText ORDER BY COUNT(AnswerText) DESC LIMIT 3 | [
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11,893 | retail_world | bird:train.json:6531 | What is the total amount of sales made in the year 1997? | SELECT SUM(T2.UnitPrice * T2.Quantity * (1 - T2.Discount)) FROM Orders AS T1 INNER JOIN `Order Details` AS T2 ON T1.OrderID = T2.OrderID WHERE T1.OrderDate LIKE '1997%' | [
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11,894 | customers_card_transactions | spider:train_spider.json:707 | How many debit cards do we have? | SELECT count(*) FROM Customers_cards WHERE card_type_code = "Debit" | [
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11,895 | manufactory_1 | spider:train_spider.json:5336 | Select the name and price of all products with a price larger than or equal to $180, and sort first by price (in descending order), and then by name (in ascending order). | SELECT name , price FROM products WHERE price >= 180 ORDER BY price DESC , name ASC | [
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11,896 | authors | bird:train.json:3558 | What is the homepage address for paper "Energy-efficiency bounds for noise-tolerant dynamic circuits"? | SELECT T2.HomePage FROM Paper AS T1 INNER JOIN Conference AS T2 ON T1.ConferenceId = T2.Id WHERE T1.Title = 'Energy-efficiency bounds for noise-tolerant dynamic circuits' | [
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11,897 | sakila_1 | spider:train_spider.json:2945 | What are the payment dates for any payments that have an amount greater than 10 or were handled by a staff member with the first name Elsa? | SELECT payment_date FROM payment WHERE amount > 10 UNION SELECT T1.payment_date FROM payment AS T1 JOIN staff AS T2 ON T1.staff_id = T2.staff_id WHERE T2.first_name = 'Elsa' | [
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11,898 | farm | spider:train_spider.json:39 | What is the status of the city that has hosted the most competitions? | SELECT T1.Status FROM city AS T1 JOIN farm_competition AS T2 ON T1.City_ID = T2.Host_city_ID GROUP BY T2.Host_city_ID ORDER BY COUNT(*) DESC LIMIT 1 | [
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11,899 | legislator | bird:train.json:4820 | What is the first name of the legislator whose address at 1005 Longworth HOB; Washington DC 20515-1408? | SELECT T1.first_name FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T2.address = '1005 Longworth HOB Washington DC 20515-1408' GROUP BY T1.first_name | [
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11,900 | pilot_record | spider:train_spider.json:2091 | Show the pilot positions that have both pilots joining after year 2005 and pilots joining before 2000. | SELECT POSITION FROM pilot WHERE Join_Year < 2000 INTERSECT SELECT POSITION FROM pilot WHERE Join_Year > 2005 | [
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11,901 | customers_and_orders | bird:test.json:255 | What is the product id and product name for the cheapest Hardware type product? | SELECT product_id , product_name FROM Products WHERE product_type_code = "Hardware" ORDER BY product_price ASC LIMIT 1 | [
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11,902 | college_1 | spider:train_spider.json:3286 | How many credits is the course that the student with the last name Smithson took, and what is its description? | SELECT T4.crs_description , T4.crs_credit FROM CLASS AS T1 JOIN enroll AS T2 ON T1.class_code = T2.class_code JOIN student AS T3 ON T3.stu_num = T2.stu_num JOIN course AS T4 ON T4.crs_code = T1.crs_code WHERE T3.stu_lname = 'Smithson' | [
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11,903 | movie_1 | spider:train_spider.json:2476 | Find the names of all reviewers who rated Gone with the Wind. | SELECT DISTINCT T3.name FROM Rating AS T1 JOIN Movie AS T2 ON T1.mID = T2.mID JOIN Reviewer AS T3 ON T1.rID = T3.rID WHERE T2.title = 'Gone with the Wind' | [
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11,904 | video_games | bird:train.json:3416 | How many games did BMG Interactive Entertainment release in 2012? | SELECT COUNT(DISTINCT T2.game_id) FROM publisher AS T1 INNER JOIN game_publisher AS T2 ON T1.id = T2.publisher_id INNER JOIN game_platform AS T3 ON T2.id = T3.game_publisher_id WHERE T3.release_year = 2012 | [
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11,905 | retail_complains | bird:train.json:307 | How many clients with the last name Alvarado are from Maryland? | SELECT COUNT(T2.client_id) FROM district AS T1 INNER JOIN client AS T2 ON T1.district_id = T2.district_id INNER JOIN state AS T3 ON T1.state_abbrev = T3.StateCode WHERE T2.last = 'Alvarado' AND T2.state = 'MD' | [
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11,906 | world | bird:train.json:7869 | What is the capital city of the country with largest population? | SELECT T1.Capital FROM Country AS T1 INNER JOIN City AS T2 ON T1.Code = T2.CountryCode ORDER BY T1.Population DESC LIMIT 1 | [
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11,907 | climbing | spider:train_spider.json:1138 | Please show the countries and the number of climbers from each country. | SELECT Country , COUNT(*) FROM climber GROUP BY Country | [
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11,908 | train_station | spider:train_spider.json:6611 | Show the name and service for all trains in order by time. | SELECT name , service FROM train ORDER BY TIME | [
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11,909 | retail_complains | bird:train.json:348 | How many clients who live in New York City have the complaint outcome as "AGENT"? | SELECT COUNT(T2.`rand client`) FROM client AS T1 INNER JOIN callcenterlogs AS T2 ON T1.client_id = T2.`rand client` WHERE T1.city = 'New York City' AND T2.outcome = 'AGENT' | [
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11,910 | books | bird:train.json:5918 | Among the books published by publisher "Thomas Nelson", how many of them have over 300 pages? | SELECT COUNT(*) FROM book AS T1 INNER JOIN publisher AS T2 ON T1.publisher_id = T2.publisher_id WHERE T2.publisher_name = 'Thomas Nelson' AND T1.num_pages > 300 | [
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11,911 | headphone_store | bird:test.json:943 | Sort all store names by store open date. | SELECT name FROM store ORDER BY date_opened | [
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11,912 | movie_1 | spider:train_spider.json:2526 | What are names of the movies that are either made before 1980 or directed by James Cameron? | SELECT title FROM Movie WHERE director = "James Cameron" OR YEAR < 1980 | [
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11,913 | works_cycles | bird:train.json:7243 | Who is the sales person in charge of the territory with the id "9"? Provide their full name. | SELECT T2.FirstName, T2.MiddleName, T2.LastName FROM SalesPerson AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE T1.TerritoryID = 9 | [
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11,914 | institution_sports | bird:test.json:1663 | List the names of institutions with at least one championship. | SELECT T2.Name FROM championship AS T1 JOIN institution AS T2 ON T1.Institution_ID = T2.Institution_ID WHERE T1.Number_of_Championships >= 1 | [
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11,915 | behavior_monitoring | spider:train_spider.json:3117 | What is the cell phone number of the student whose address has the lowest monthly rental? | SELECT T2.cell_mobile_number FROM Student_Addresses AS T1 JOIN Students AS T2 ON T1.student_id = T2.student_id ORDER BY T1.monthly_rental ASC LIMIT 1 | [
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11,916 | student_loan | bird:train.json:4482 | What is the ratio of students who have payment due and those who do not have payment due? | SELECT CAST(SUM(IIF(`bool` = 'pos', 1, 0)) AS REAL) / SUM(IIF(`bool` = 'neg', 1, 0)) FROM no_payment_due | [
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11,917 | bike_1 | spider:train_spider.json:183 | List all the cities in a decreasing order of each city's stations' highest latitude. | SELECT city FROM station GROUP BY city ORDER BY max(lat) DESC | [
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11,918 | insurance_fnol | spider:train_spider.json:912 | Tell me the types of the policy used by the customer named "Dayana Robel". | SELECT DISTINCT t3.policy_type_code FROM customers AS t1 JOIN customers_policies AS t2 ON t1.customer_id = t2.customer_id JOIN available_policies AS t3 ON t2.policy_id = t3.policy_id WHERE t1.customer_name = "Dayana Robel" | [
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11,919 | toxicology | bird:dev.json:331 | How many of the molecules are carcinogenic? | SELECT COUNT(T.molecule_id) FROM molecule AS T WHERE T.label = '+' | [
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11,920 | movie_3 | bird:train.json:9421 | How many times has Mary Smith rented a film? | SELECT COUNT(T1.customer_id) FROM payment AS T1 INNER JOIN customer AS T2 ON T1.customer_id = T2.customer_id WHERE T2.first_name = 'MARY' AND T2.last_name = 'SMITH' | [
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11,921 | superhero | bird:dev.json:817 | Give the race of the blue-haired male superhero. | SELECT T3.race FROM superhero AS T1 INNER JOIN colour AS T2 ON T1.hair_colour_id = T2.id INNER JOIN race AS T3 ON T1.race_id = T3.id INNER JOIN gender AS T4 ON T1.gender_id = T4.id WHERE T2.colour = 'Blue' AND T4.gender = 'Male' | [
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11,922 | music_1 | spider:train_spider.json:3558 | What countries are the female artists who sung in the language Bangla from? | SELECT T1.country FROM artist AS T1 JOIN song AS T2 ON T1.artist_name = T2.artist_name WHERE T1.gender = "Female" AND T2.languages = "bangla" | [
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11,923 | college_1 | spider:train_spider.json:3179 | What are the first names and date of birth of professors teaching course ACCT-211? | SELECT DISTINCT T1.EMP_FNAME , T1.EMP_DOB FROM employee AS T1 JOIN CLASS AS T2 ON T1.EMP_NUM = T2.PROF_NUM WHERE CRS_CODE = "ACCT-211" | [
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11,924 | mondial_geo | bird:train.json:8263 | What is the highest infant mortality rate per thousand of the countries whose inflation is under 3? | SELECT MAX(T2.Infant_Mortality) FROM economy AS T1 INNER JOIN population AS T2 ON T1.Country = T2.Country WHERE T1.Inflation < 3 | [
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11,925 | products_gen_characteristics | spider:train_spider.json:5596 | What are the names, details and data types of the characteristics which are never used by any product? | SELECT characteristic_name , other_characteristic_details , characteristic_data_type FROM CHARACTERISTICS EXCEPT SELECT t1.characteristic_name , t1.other_characteristic_details , t1.characteristic_data_type FROM CHARACTERISTICS AS t1 JOIN product_characteristics AS t2 ON t1.characteristic_id = t2.characteristic_i... | [
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11,926 | retails | bird:train.json:6855 | Calculate the percentage of countries that belong to the American region. | SELECT CAST(SUM(IIF(T1.r_name = 'America', 1, 0)) AS REAL) * 100 / COUNT(T2.n_name) FROM region AS T1 INNER JOIN nation AS T2 ON T1.r_regionkey = T2.n_regionkey | [
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11,927 | e_learning | spider:train_spider.json:3795 | What are the names of all the subjects. | SELECT subject_name FROM SUBJECTS | [
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11,928 | tracking_grants_for_research | spider:train_spider.json:4394 | What are the descriptions of all the project outcomes? | SELECT T1.outcome_description FROM Research_outcomes AS T1 JOIN Project_outcomes AS T2 ON T1.outcome_code = T2.outcome_code | [
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11,929 | hospital_1 | spider:train_spider.json:3981 | What are the procedures that cost more than 1000 or are specialized in by physician John Wen? | SELECT name FROM procedures WHERE cost > 1000 UNION SELECT T3.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 T1.name = "John Wen" | [
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11,930 | chicago_crime | bird:train.json:8597 | Among all the crimes that had happened in Central Chicago, how many of them were cases of domestic violence? | SELECT COUNT(*) FROM Crime AS T1 INNER JOIN District AS T2 ON T1.district_no = T2.district_no WHERE T2.district_name = 'Central' AND T1.domestic = 'TRUE' | [
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11,932 | european_football_1 | bird:train.json:2785 | Which team won the match of the Bundesliga division on 2020/10/2? | SELECT CASE WHEN T1.FTR = 'H' THEN T1.HomeTeam WHEN T1.FTR = 'A' THEN T1.AwayTeam END WINNER FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T1.Date = '2020-10-02' AND T2.name = 'Bundesliga' | [
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11,933 | retails | bird:train.json:6901 | How many urgent orders did Clerk#000000001 handle in 1997? | SELECT COUNT(o_orderkey) FROM orders WHERE STRFTIME('%Y', o_orderdate) = '1997' AND o_clerk = 'Clerk#000000001' AND o_orderpriority = '1-URGENT' | [
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11,934 | inn_1 | spider:train_spider.json:2586 | How many kids stay in the room DAMIEN TRACHSEL checked in on Sep 21, 2010? | SELECT Kids FROM Reservations WHERE CheckIn = "2010-09-21" AND FirstName = "DAMIEN" AND LastName = "TRACHSEL"; | [
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11,935 | car_retails | bird:train.json:1666 | Which 5 products has the lowest amount of orders? List the product names. | SELECT t2.productName FROM orderdetails AS t1 INNER JOIN products AS t2 ON t1.productCode = t2.productCode GROUP BY t2.productName ORDER BY SUM(t1.quantityOrdered) ASC LIMIT 5 | [
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11,937 | menu | bird:train.json:5570 | Please list the names of all the dishes on page 1 of menu ID12882. | SELECT T3.name FROM MenuPage AS T1 INNER JOIN MenuItem AS T2 ON T1.id = T2.menu_page_id INNER JOIN Dish AS T3 ON T2.dish_id = T3.id WHERE T1.menu_id = 12882 AND T1.page_number = 1 | [
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11,938 | card_games | bird:dev.json:521 | Among the cards whose version of frame style is 1997, what is the status of the card illustrated by D. Alexander Gregory in legacy play format that has sensitive content or Wizards of the Coast? | SELECT DISTINCT T2.status FROM cards AS T1 INNER JOIN legalities AS T2 ON T2.uuid = T1.uuid WHERE T1.frameVersion = 1997 AND T1.hasContentWarning = 1 AND T1.artist = 'D. Alexander Gregory' AND T2.format = 'legacy' | [
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11,939 | movie_platform | bird:train.json:52 | Where can I find the movie list "Short and pretty damn sweet"? | SELECT list_url FROM lists WHERE list_title = 'Short and pretty damn sweet' | [
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11,940 | mondial_geo | bird:train.json:8411 | Of all the countries in which English is spoken, what percentage has English as their only language? | SELECT CAST(SUM(CASE WHEN T2.Percentage = 100 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.Name) FROM country AS T1 INNER JOIN language AS T2 ON T1.Code = T2.Country WHERE T2.Name = 'English' | [
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11,941 | coinmarketcap | bird:train.json:6263 | Which crytocurrency was ranked the first by CoinMarketCap on 2013/4/28? | SELECT T1.name FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T2.date = '2013-04-28' AND T2.cmc_rank = 1 | [
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11,942 | synthea | bird:train.json:1445 | Calculate the average age of patients with prediabetes care plan. | SELECT CAST(SUM(CASE WHEN T1.deathdate IS NULL THEN strftime('%Y', T2.STOP) - strftime('%Y', T1.birthdate) ELSE strftime('%Y', T1.deathdate) - strftime('%Y', T1.birthdate) END) AS REAL) / COUNT(DISTINCT T1.patient) FROM patients AS T1 INNER JOIN careplans AS T2 ON T1.patient = T2.PATIENT WHERE T2.REASONDESCRIPTION = 'P... | [
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11,943 | manufactory_1 | spider:train_spider.json:5317 | How many products are not made by Sony? | SELECT count(DISTINCT name) FROM products WHERE name NOT IN (SELECT T1.name FROM products AS T1 JOIN manufacturers AS T2 ON T1.Manufacturer = T2.code WHERE T2.name = 'Sony') | [
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11,944 | insurance_policies | spider:train_spider.json:3859 | Find the claimed amount in the claim with the least amount settled. Show both the settlement amount and claim amount. | SELECT Amount_Settled , Amount_Claimed FROM Claims ORDER BY Amount_Settled ASC LIMIT 1 | [
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11,947 | bike_1 | spider:train_spider.json:122 | What is the total and maximum duration for all trips with the bike id 636? | SELECT sum(duration) , max(duration) FROM trip WHERE bike_id = 636 | [
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11,948 | candidate_poll | spider:train_spider.json:2421 | Give the names of people who did not participate in the candidate election. | SELECT name FROM people WHERE people_id NOT IN (SELECT people_id FROM candidate) | [
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11,949 | car_retails | bird:train.json:1574 | Determine the email and Code of employee who are working at United State, state MA | SELECT T1.email, T1.employeeNumber FROM employees AS T1 INNER JOIN offices AS T2 ON T1.officeCode = T2.officeCode WHERE T2.state = 'MA' AND T2.country = 'USA' | [
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11,950 | cre_Docs_and_Epenses | spider:train_spider.json:6395 | Show all statement id and the number of accounts for each statement. | SELECT STATEMENT_ID , count(*) FROM Accounts GROUP BY STATEMENT_ID | [
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11,951 | flight_1 | spider:train_spider.json:433 | Show the name and distance of the aircrafts with more than 5000 distance and which at least 5 people have its certificate. | SELECT T2.name FROM Certificate AS T1 JOIN Aircraft AS T2 ON T2.aid = T1.aid WHERE T2.distance > 5000 GROUP BY T1.aid ORDER BY count(*) >= 5 | [
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11,952 | student_loan | bird:train.json:4405 | List out student IDs that have the longest absence duration from school. | SELECT name FROM longest_absense_from_school WHERE `month` = ( SELECT MAX(month) FROM longest_absense_from_school ) | [
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11,953 | car_retails | bird:train.json:1630 | How many sales representitives are based in the offices in the USA? | SELECT COUNT(t1.employeeNumber) FROM employees AS t1 INNER JOIN offices AS t2 ON t1.officeCode = t2.officeCode WHERE t2.country = 'USA' AND t1.jobTitle = 'Sales Rep' | [
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11,954 | retail_complains | bird:train.json:269 | What was the phone of number of the client who made the complaint call "CR0100432" ？ | SELECT T1.phone FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Complaint ID` = 'CR0100432' | [
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11,956 | music_1 | spider:train_spider.json:3561 | What is the number of artists for each gender? | SELECT count(*) , gender FROM artist GROUP BY gender | [
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11,957 | csu_1 | spider:train_spider.json:2342 | Find the count of universities whose campus fee is greater than the average campus fee. | SELECT count(*) FROM csu_fees WHERE campusfee > (SELECT avg(campusfee) FROM csu_fees) | [
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11,958 | sakila_1 | spider:train_spider.json:2938 | Which film is rented at a fee of 0.99 and has less than 3 in the inventory? List the film title and id. | SELECT title , film_id FROM film WHERE rental_rate = 0.99 INTERSECT SELECT T1.title , T1.film_id FROM film AS T1 JOIN inventory AS T2 ON T1.film_id = T2.film_id GROUP BY T1.film_id HAVING count(*) < 3 | [
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11,960 | menu | bird:train.json:5509 | List down the locations of menu sponsored by Norddeutscher Lloyd Bremen. | SELECT location FROM Menu WHERE sponsor = 'Norddeutscher Lloyd Bremen' | [
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11,961 | aan_1 | bird:test.json:979 | Find all papers with titles and paper IDs written by Mckeown. | SELECT T1.title , T1.paper_id FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Author AS T3 ON T3.author_id = T2.author_id WHERE T3.name LIKE "%Mckeown%" | [
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11,962 | customers_and_addresses | spider:train_spider.json:6079 | How many customers are living in city "Lake Geovannyton"? | SELECT count(*) 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.city = "Lake Geovannyton" | [
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11,963 | bike_share_1 | bird:train.json:9040 | How many stations in San Francisco are installed in 2014? | SELECT SUM(CASE WHEN city = 'San Francisco' AND SUBSTR(installation_date, -4) = '2014' THEN 1 ELSE 0 END) FROM station | [
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11,964 | cre_Theme_park | spider:train_spider.json:5922 | Which tourist attractions are related to royal family? Tell me their details and how we can get there. | SELECT T1.Royal_Family_Details , T2.How_to_Get_There FROM ROYAL_FAMILY AS T1 JOIN TOURIST_ATTRACTIONS AS T2 ON T1.Royal_Family_ID = T2.Tourist_Attraction_ID | [
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11,965 | game_1 | spider:train_spider.json:6043 | Show the game name that has most number of hours played. | SELECT gname FROM Plays_games AS T1 JOIN Video_games AS T2 ON T1.gameid = T2.gameid GROUP BY T1.gameid ORDER BY sum(hours_played) DESC LIMIT 1 | [
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11,966 | app_store | bird:train.json:2535 | What are the apps with only 5,000+ installs? | SELECT DISTINCT App FROM playstore WHERE Installs = '5,000+' | [
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11,967 | student_assessment | spider:train_spider.json:107 | List the id of students who attended statistics courses in the order of attendance date. | SELECT T2.student_id FROM courses AS T1 JOIN student_course_attendance AS T2 ON T1.course_id = T2.course_id WHERE T1.course_name = "statistics" ORDER BY T2.date_of_attendance | [
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11,969 | mountain_photos | spider:train_spider.json:3718 | What are the id and name of the mountains that have at least 2 photos? | SELECT T1.id , T1.name FROM mountain AS T1 JOIN photos AS T2 ON T1.id = T2.mountain_id GROUP BY T1.id HAVING count(*) >= 2 | [
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11,970 | book_publishing_company | bird:train.json:186 | Who are the employees working for publisher not located in USA? State the employee's name and publisher name. | SELECT T1.fname, T1.lname, T2.pub_name FROM employee AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T2.country != 'USA' | [
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11,971 | university_basketball | spider:train_spider.json:1009 | Find how many school locations have the word 'NY'. | SELECT count(*) FROM university WHERE LOCATION LIKE "%NY%" | [
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11,972 | codebase_community | bird:dev.json:594 | Which user created post ID 1 and what is the reputation of this user? | SELECT T2.Id, T2.Reputation FROM comments AS T1 INNER JOIN users AS T2 ON T1.UserId = T2.Id WHERE T1.PostId = 1 | [
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11,973 | menu | bird:train.json:5558 | Please list the IDs of all the menus that are DIYs of the restaurant. | SELECT id FROM Menu WHERE sponsor IS NULL | [
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"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": ... | [
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
11,974 | warehouse_1 | bird:test.json:1740 | What is the total capacity of all warehouses? | SELECT sum(capacity) FROM warehouses | [
"What",
"is",
"the",
"total",
"capacity",
"of",
"all",
"warehouses",
"?"
] | [
{
"id": 0,
"type": "table",
"value": "warehouses"
},
{
"id": 1,
"type": "column",
"value": "capacity"
}
] | [
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"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": ... | [
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
11,975 | works_cycles | bird:train.json:7185 | State the full name of accountants in the company. | SELECT T2.FirstName, T2.MiddleName, T2.LastName FROM Employee AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE T1.JobTitle = 'Accountant' | [
"State",
"the",
"full",
"name",
"of",
"accountants",
"in",
"the",
"company",
"."
] | [
{
"id": 7,
"type": "column",
"value": "businessentityid"
},
{
"id": 1,
"type": "column",
"value": "middlename"
},
{
"id": 6,
"type": "value",
"value": "Accountant"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 2,
"type": "colu... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
... | [
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
11,976 | citeseer | bird:train.json:4143 | Among all the DB class type citation, which word is the most frequently cited? | SELECT T2.word_cited_id FROM paper AS T1 INNER JOIN content AS T2 ON T1.paper_id = T2.paper_id WHERE T1.class_label = 'DB' GROUP BY T2.word_cited_id ORDER BY COUNT(T2.word_cited_id) DESC LIMIT 1 | [
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"class",
"type",
"citation",
",",
"which",
"word",
"is",
"the",
"most",
"frequently",
"cited",
"?"
] | [
{
"id": 0,
"type": "column",
"value": "word_cited_id"
},
{
"id": 3,
"type": "column",
"value": "class_label"
},
{
"id": 5,
"type": "column",
"value": "paper_id"
},
{
"id": 2,
"type": "table",
"value": "content"
},
{
"id": 1,
"type": "table",
... | [
{
"entity_id": 0,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"... | [
"O",
"O",
"O",
"B-VALUE",
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"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O"
] |
11,977 | aan_1 | bird:test.json:1040 | What is the name of the affiliation which publishes the greatest number of papers among those whose address contains 'China'. | SELECT T1.name FROM Affiliation AS T1 JOIN Author_list AS T2 ON T1.affiliation_id = T2.affiliation_id WHERE T1.address LIKE "%China%" GROUP BY T1.affiliation_id ORDER BY count(*) DESC LIMIT 1 | [
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"the",
"name",
"of",
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"which",
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"among",
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"whose",
"address",
"contains",
"'",
"China",
"'",
"."
] | [
{
"id": 0,
"type": "column",
"value": "affiliation_id"
},
{
"id": 2,
"type": "table",
"value": "affiliation"
},
{
"id": 3,
"type": "table",
"value": "author_list"
},
{
"id": 4,
"type": "column",
"value": "address"
},
{
"id": 5,
"type": "column"... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
"entity_id": 5,
... | [
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"O",
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"O",
"O",
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
11,978 | customers_and_orders | bird:test.json:279 | Show all customer names with the payment method code used by least number of customers. | SELECT customer_name FROM Customers WHERE payment_method_code = ( SELECT payment_method_code FROM Customers GROUP BY payment_method_code ORDER BY count(*) ASC LIMIT 1) | [
"Show",
"all",
"customer",
"names",
"with",
"the",
" ",
"payment",
"method",
"code",
"used",
"by",
"least",
"number",
"of",
"customers",
"."
] | [
{
"id": 2,
"type": "column",
"value": "payment_method_code"
},
{
"id": 1,
"type": "column",
"value": "customer_name"
},
{
"id": 0,
"type": "table",
"value": "customers"
}
] | [
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
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7,
8,
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
... | [
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"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
11,979 | party_host | spider:train_spider.json:2676 | Show the nations that have both hosts older than 45 and hosts younger than 35. | SELECT Nationality FROM HOST WHERE Age > 45 INTERSECT SELECT Nationality FROM HOST WHERE Age < 35 | [
"Show",
"the",
"nations",
"that",
"have",
"both",
"hosts",
"older",
"than",
"45",
"and",
"hosts",
"younger",
"than",
"35",
"."
] | [
{
"id": 1,
"type": "column",
"value": "nationality"
},
{
"id": 0,
"type": "table",
"value": "host"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 3,
"type": "value",
"value": "45"
},
{
"id": 4,
"type": "value",
"value": "35"
}
... | [
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
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3
]
},
{
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},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
... | [
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"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
11,980 | retail_world | bird:train.json:6587 | Indicate the fax of the company Blondesddsl pre et fils in Strasbourg city. | SELECT Fax FROM Customers WHERE CompanyName = 'Blondesddsl pre et fils' AND City = 'Strasbourg' | [
"Indicate",
"the",
"fax",
"of",
"the",
"company",
"Blondesddsl",
"pre",
"et",
"fils",
"in",
"Strasbourg",
"city",
"."
] | [
{
"id": 3,
"type": "value",
"value": "Blondesddsl pre et fils"
},
{
"id": 2,
"type": "column",
"value": "companyname"
},
{
"id": 5,
"type": "value",
"value": "Strasbourg"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 4,
"type":... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
6,
7,
8,
9
]
},
{
"entity_id": 4,
"token_idxs": [
12... | [
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
11,981 | talkingdata | bird:train.json:1234 | What is the percentage of users who are in the same behavior category as "Academic Information"? | SELECT SUM(IIF(T1.category = 'Academic Information', 1.0, 0)) / COUNT(T2.app_id) AS per FROM label_categories AS T1 INNER JOIN app_labels AS T2 ON T1.label_id = T2.label_id | [
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"is",
"the",
"percentage",
"of",
"users",
"who",
"are",
"in",
"the",
"same",
"behavior",
"category",
"as",
"\"",
"Academic",
"Information",
"\"",
"?"
] | [
{
"id": 7,
"type": "value",
"value": "Academic Information"
},
{
"id": 0,
"type": "table",
"value": "label_categories"
},
{
"id": 1,
"type": "table",
"value": "app_labels"
},
{
"id": 2,
"type": "column",
"value": "label_id"
},
{
"id": 6,
"type"... | [
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
11,982 | cars | bird:train.json:3109 | Among the cars produced in year 1973, how many of the cars have horsepower less than 100? | SELECT COUNT(*) FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID WHERE T2.model_year = 1973 AND T1.horsepower < 100 | [
"Among",
"the",
"cars",
"produced",
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",",
"how",
"many",
"of",
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"?"
] | [
{
"id": 1,
"type": "table",
"value": "production"
},
{
"id": 3,
"type": "column",
"value": "model_year"
},
{
"id": 5,
"type": "column",
"value": "horsepower"
},
{
"id": 0,
"type": "table",
"value": "data"
},
{
"id": 4,
"type": "value",
"val... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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3,
4
]
},
{
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},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"toke... | [
"O",
"O",
"O",
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"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
11,983 | advertising_agencies | bird:test.json:2102 | What are all meeting outcomes and purposes? | SELECT meeting_outcome , purpose_of_meeting FROM meetings | [
"What",
"are",
"all",
"meeting",
"outcomes",
"and",
"purposes",
"?"
] | [
{
"id": 2,
"type": "column",
"value": "purpose_of_meeting"
},
{
"id": 1,
"type": "column",
"value": "meeting_outcome"
},
{
"id": 0,
"type": "table",
"value": "meetings"
}
] | [
{
"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": ... | [
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O"
] |
11,984 | public_review_platform | bird:train.json:3915 | How many of the businesses are active? | SELECT COUNT(business_id) FROM Business WHERE active LIKE 'True' | [
"How",
"many",
"of",
"the",
"businesses",
"are",
"active",
"?"
] | [
{
"id": 3,
"type": "column",
"value": "business_id"
},
{
"id": 0,
"type": "table",
"value": "business"
},
{
"id": 1,
"type": "column",
"value": "active"
},
{
"id": 2,
"type": "value",
"value": "True"
}
] | [
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"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",
"B-COLUMN",
"O"
] |
11,985 | movies_4 | bird:train.json:446 | How many movies did Universal Studios release? | SELECT COUNT(T2.movie_id) FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id WHERE T1.company_name = 'Universal Studios' | [
"How",
"many",
"movies",
"did",
"Universal",
"Studios",
"release",
"?"
] | [
{
"id": 0,
"type": "table",
"value": "production_company"
},
{
"id": 3,
"type": "value",
"value": "Universal Studios"
},
{
"id": 1,
"type": "table",
"value": "movie_company"
},
{
"id": 2,
"type": "column",
"value": "company_name"
},
{
"id": 5,
... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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},
{
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4,
5
]
},
{
"entity_id": 4,
"token_idxs": [
2,
3
]
},
{
"entity_id": 5,
... | [
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
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