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3,864 | public_review_platform | bird:train.json:4064 | How many businesses with the category named Stadiums & Arenas are rated highest? | SELECT COUNT(T1.business_id) FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business AS T3 ON T1.business_id = T3.business_id WHERE T2.category_name = 'Stadiums & Arenas' AND T3.stars = ( SELECT MAX(stars) FROM Business ) | [
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3,865 | legislator | bird:train.json:4781 | Which legislator has the YouTube channel 'RoskamIL06?' Write the official full name. | SELECT T1.official_full_name FROM current AS T1 INNER JOIN `social-media` AS T2 ON T2.bioguide = T1.bioguide_id WHERE T2.youtube = 'RoskamIL06' | [
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3,866 | soccer_2016 | bird:train.json:1858 | How many players got out in the first inning of match ID "548335"? | SELECT SUM(CASE WHEN Match_Id = 548335 THEN 1 ELSE 0 END) FROM Wicket_Taken WHERE Innings_No = 1 | [
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3,867 | local_govt_and_lot | spider:train_spider.json:4847 | List the id and type of each thing, and the details of the organization that owns it. | SELECT T1.thing_id , T1.type_of_Thing_Code , T2.organization_details FROM Things AS T1 JOIN Organizations AS T2 ON T1.organization_id = T2.organization_id | [
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3,868 | retail_world | bird:train.json:6579 | What is the salary range for sales representative in Northwind? | SELECT ( SELECT MIN(Salary) FROM Employees WHERE Title = 'Sales Representative' ) AS MIN , ( SELECT MAX(Salary) FROM Employees WHERE Title = 'Sales Representative' ) AS MAX | [
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3,869 | world | bird:train.json:7914 | Provide the language used in the country ruled by Pierre Buyoya. | SELECT T1.Language FROM CountryLanguage AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.Code WHERE T2.HeadOfState = 'Pierre Buyoya' | [
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3,870 | customers_and_addresses | spider:train_spider.json:6076 | Which product's detail contains the word "Latte" or "Americano"? Return the full detail. | SELECT product_details FROM products WHERE product_details LIKE "%Latte%" OR product_details LIKE "%Americano%" | [
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3,871 | simpson_episodes | bird:train.json:4343 | What is the awarded category that the awarded character Lenny won? | SELECT DISTINCT T1.award_category FROM Award AS T1 INNER JOIN Character_Award AS T2 ON T1.award_id = T2.award_id WHERE T2.character = 'Lenny'; | [
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3,873 | cookbook | bird:train.json:8882 | Give the name of the most widely used ingredient. | SELECT T1.name FROM Ingredient AS T1 INNER JOIN Quantity AS T2 ON T1.ingredient_id = T2.ingredient_id GROUP BY T1.name ORDER BY COUNT(T1.name) DESC LIMIT 1 | [
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3,874 | university_rank | bird:test.json:1763 | What is the maximum, average, and minimum enrollment for universities? | SELECT max(enrollment) , avg(enrollment) , min(enrollment) FROM University | [
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3,875 | card_games | bird:dev.json:484 | Please list the Italian names of the cards in the set Coldsnap with the highest converted mana cost. | SELECT T2.name FROM foreign_data AS T1 INNER JOIN cards AS T2 ON T2.uuid = T1.uuid INNER JOIN sets AS T3 ON T3.code = T2.setCode WHERE T3.name = 'Coldsnap' AND T1.language = 'Italian' ORDER BY T2.convertedManaCost DESC | [
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3,876 | video_games | bird:train.json:3355 | What is the genre ID of the game named 25 to Life? | SELECT T.genre_id FROM game AS T WHERE T.game_name = '25 to Life' | [
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3,877 | movies_4 | bird:train.json:521 | What is the iso code of "Kyrgyz Republic"? | SELECT COUNTry_iso_code FROM COUNTry WHERE COUNTry_name = 'Kyrgyz Republic' | [
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3,879 | public_review_platform | bird:train.json:4030 | Calculate the percentage of businesses who located in Mesa. What is attribute value of these businesses. | SELECT CAST(COUNT(T1.city) AS REAL) * 100 / ( SELECT COUNT(business_id) FROM Business ), T2.attribute_value FROM Business AS T1 INNER JOIN Business_Attributes AS T2 ON T1.business_id = T2.business_id WHERE T1.city = 'Mesa' | [
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3,880 | bakery_1 | bird:test.json:1560 | What are the minimum and maximum prices of food goods, ordered by food? | SELECT min(price) , max(price) , food FROM goods GROUP BY food ORDER BY food | [
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] |
3,881 | wine_1 | spider:train_spider.json:6577 | What are the average price and score of wines grouped by appelation? | SELECT avg(Price) , avg(Score) , Appelation FROM WINE GROUP BY Appelation | [
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{
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{
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3,882 | bakery_1 | bird:test.json:1582 | Give the flavors of Cakes that are not available for Tart. | SELECT DISTINCT flavor FROM goods WHERE food = "Cake" EXCEPT SELECT DISTINCT flavor FROM goods WHERE food = "Tart" | [
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"id": 4,
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3,883 | card_games | bird:dev.json:467 | How many cards are there in the base set of "Hauptset Zehnte Edition"? | SELECT T1.baseSetSize FROM sets AS T1 INNER JOIN set_translations AS T2 ON T2.setCode = T1.code WHERE T2.translation = 'Hauptset Zehnte Edition' | [
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"id": 4,
"type": "value",
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{
"id": 3,
"type": "column",
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{
"id": 5,
... | [
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3,884 | works_cycles | bird:train.json:7256 | What is the total amount due of all the purchases made by the company to the vendor that has the lowest selling price amount of a single product? Indicate the name of the vendor to which the purchases was made. | SELECT T1.UnitPrice, T3.Name FROM PurchaseOrderDetail AS T1 INNER JOIN PurchaseOrderHeader AS T2 ON T1.PurchaseOrderID = T2.PurchaseOrderID INNER JOIN Vendor AS T3 ON T2.VendorID = T3.BusinessEntityID ORDER BY T1.UnitPrice LIMIT 1 | [
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3,885 | car_road_race | bird:test.json:1329 | What are the names of drivers, ordered descending alphabetically? | SELECT Driver_Name FROM driver ORDER BY Driver_Name DESC | [
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3,886 | school_bus | spider:train_spider.json:6357 | Show the names of the drivers without a school bus. | SELECT name FROM driver WHERE driver_id NOT IN (SELECT driver_id FROM school_bus) | [
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{
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3,887 | movie_3 | bird:train.json:9357 | Who are the actors of film titled "BIRD INDEPENDENCE"? | SELECT T3.first_name, T3.last_name FROM film AS T1 INNER JOIN film_actor AS T2 ON T1.film_id = T2.film_id INNER JOIN actor AS T3 ON T2.actor_id = T3.actor_id WHERE T1.title = 'BIRD INDEPENDENCE' | [
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{
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"type": "column",
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3,888 | language_corpus | bird:train.json:5700 | In Abadia, what is the word id of the of the Catalan language that appeared the highest amount of times? Indicate the how many times did they said word id appeared. | SELECT T2.wid, T2.occurrences FROM pages AS T1 INNER JOIN pages_words AS T2 ON T1.pid = T2.pid WHERE T1.title = 'Abadia' ORDER BY T2.occurrences DESC LIMIT 1 | [
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"... | [
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3,889 | entrepreneur | spider:train_spider.json:2295 | List the names of people that are not entrepreneurs. | SELECT Name FROM people WHERE People_ID NOT IN (SELECT People_ID FROM entrepreneur) | [
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"type": "table",
"value": "people"
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{
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3,890 | toxicology | bird:dev.json:224 | What are the bond IDs that have the same atom ID 2 of TR000_2? | SELECT T.bond_id FROM connected AS T WHERE T.atom_id2 = 'TR000_2' | [
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"type": "column",
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{
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"value": "TR000_2"
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3,891 | soccer_2 | spider:train_spider.json:5001 | What are the names of all students who tried out in alphabetical order? | SELECT T1.pName FROM player AS T1 JOIN tryout AS T2 ON T1.pID = T2.pID ORDER BY T1.pName | [
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{
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3,892 | sales | bird:train.json:5437 | What is the price and quantity of the product named Seat Tube? | SELECT DISTINCT T2.Price, T1.Quantity FROM Sales AS T1 INNER JOIN Products AS T2 ON T1.ProductID = T2.ProductID WHERE T2.Name = 'Seat Tube' | [
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] |
3,893 | legislator | bird:train.json:4744 | To which current legislator does twitter ID234128524 belong? Please give his or her full official name. | SELECT T1.official_full_name FROM current AS T1 INNER JOIN `social-media` AS T2 ON T2.bioguide = T1.bioguide_id WHERE T2.twitter_id = 234128524 | [
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3,894 | talkingdata | bird:train.json:1057 | What were the locations of the events on 8th May, 2016? | SELECT longitude, latitude FROM `events` WHERE SUBSTR(`timestamp`, 1, 10) = '2016-05-08' | [
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{
"id": 4,
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{
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"type": "column",
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{
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"... | [
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3,895 | pilot_1 | bird:test.json:1124 | Return the names of planes owned by the pilot whose name is Smith and is 41 years old. | SELECT plane_name FROM pilotskills WHERE pilot_name = 'Smith' AND age = 41 | [
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3,896 | sales_in_weather | bird:train.json:8139 | What is the ID of the item that sold the best on 2012/1/1 in store no.1? | SELECT item_nbr FROM sales_in_weather WHERE `date` = '2012-01-01' AND store_nbr = 1 ORDER BY units DESC LIMIT 1 | [
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3,897 | bike_1 | spider:train_spider.json:114 | For each city, what is the highest latitude for its stations? | SELECT city , max(lat) FROM station GROUP BY city | [
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3,898 | train_station | spider:train_spider.json:6621 | List the names and locations of all stations ordered by their yearly entry exit and interchange amounts. | SELECT name , LOCATION FROM station ORDER BY Annual_entry_exit , Annual_interchanges | [
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3,900 | music_1 | spider:train_spider.json:3566 | What is the gender and name of the artist who sang the song with the smallest resolution? | SELECT T1.gender , T1.artist_name FROM artist AS T1 JOIN song AS T2 ON T1.artist_name = T2.artist_name ORDER BY T2.resolution LIMIT 1 | [
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3,901 | cre_Students_Information_Systems | bird:test.json:485 | How many courses do students take at most? Also find the id of the student who takes the most courses. | SELECT count(*) , student_id FROM Classes GROUP BY student_id ORDER BY count(*) DESC LIMIT 1 | [
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3,902 | manufactory_1 | spider:train_spider.json:5273 | Return the founder of Sony. | SELECT founder FROM manufacturers WHERE name = 'Sony' | [
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"id": 0,
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3,903 | music_1 | spider:train_spider.json:3546 | What is the count of the songs that last approximately 4 minutes? | SELECT count(*) FROM files WHERE duration LIKE "4:%" | [
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3,904 | public_review_platform | bird:train.json:4015 | Identify the operating hours of businesses in Black Canyon City with review count greater than average. | SELECT T2.opening_time, T2.closing_time FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id INNER JOIN Days AS T3 ON T2.day_id = T3.day_id WHERE T1.city = 'Black Canyon City' GROUP BY t2.business_id HAVING T1.review_count > AVG(T1.review_count) | [
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3,905 | student_club | bird:dev.json:1315 | How many students of the Student_Club have attended the event "Women's Soccer"? | SELECT COUNT(T1.event_id) FROM event AS T1 INNER JOIN attendance AS T2 ON T1.event_id = T2.link_to_event WHERE T1.event_name = 'Women''s Soccer' | [
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3,906 | simpson_episodes | bird:train.json:4231 | Name the title of the episode that received the highest star score and the highest number of votes. | SELECT T1.title FROM Episode AS T1 INNER JOIN Vote AS T2 ON T2.episode_id = T1.episode_id ORDER BY T2.stars DESC, T2.votes DESC LIMIT 1; | [
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3,907 | college_2 | spider:train_spider.json:1472 | Find the names of all instructors whose name includes the substring “dar”. | SELECT name FROM instructor WHERE name LIKE '%dar%' | [
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3,908 | retail_complains | bird:train.json:306 | How many complaints were served in 5 minutes or less by DORIT and responded to the customer with an explanation, were made by phone? | SELECT COUNT(T1.`Complaint ID`) FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T1.ser_time < '00:05:00' AND T1.server = 'DORIT' AND T2.`Submitted via` = 'Phone' AND T2.`Company response to consumer` = 'Closed with explanation' | [
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3,909 | game_1 | spider:train_spider.json:6021 | Show student ids who don't have any sports. | SELECT StuID FROM Student EXCEPT SELECT StuID FROM Sportsinfo | [
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3,911 | video_games | bird:train.json:3492 | Provide the name of game produced by 505 Games in 2006. | SELECT T3.game_name FROM game_platform AS T1 INNER JOIN game_publisher AS T2 ON T1.game_publisher_id = T2.id INNER JOIN game AS T3 ON T2.game_id = T3.id INNER JOIN publisher AS T4 ON T2.publisher_id = T4.id WHERE T4.publisher_name = '505 Games' AND T1.release_year = 2006 | [
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3,912 | cre_Docs_and_Epenses | spider:train_spider.json:6426 | What are the codes, names, and descriptions of the different document types? | SELECT document_type_code , document_type_name , document_type_description FROM Ref_document_types | [
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3,913 | address | bird:train.json:5139 | Which CBSAs have more than 10 zip codes? | SELECT T1.CBSA_name FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA GROUP BY T1.CBSA HAVING COUNT(T2.zip_code) > 10 | [
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3,914 | bike_1 | spider:train_spider.json:200 | What are the dates that have an average sea level pressure between 30.3 and 31? | SELECT date FROM weather WHERE mean_sea_level_pressure_inches BETWEEN 30.3 AND 31 | [
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3,915 | scientist_1 | spider:train_spider.json:6503 | Find the name of scientists who are assigned to some project. | SELECT T2.name FROM assignedto AS T1 JOIN scientists AS T2 ON T1.scientist = T2.ssn | [
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3,916 | california_schools | bird:dev.json:12 | Among the schools with an SAT excellence rate of over 0.3, what is the highest eligible free rate for students aged 5-17? | SELECT MAX(CAST(T1.`Free Meal Count (Ages 5-17)` AS REAL) / T1.`Enrollment (Ages 5-17)`) FROM frpm AS T1 INNER JOIN satscores AS T2 ON T1.CDSCode = T2.cds WHERE CAST(T2.NumGE1500 AS REAL) / T2.NumTstTakr > 0.3 | [
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3,917 | address | bird:train.json:5181 | What is the name of the CBSA of the city with the highest average house value? | SELECT DISTINCT T1.CBSA_name FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T2.avg_house_value = ( SELECT MAX(avg_house_value) FROM zip_data ) LIMIT 1 | [
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3,918 | customers_and_invoices | spider:train_spider.json:1624 | How many different products correspond to each order id? | SELECT order_id , count(DISTINCT product_id) FROM Order_items GROUP BY order_id | [
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3,920 | soccer_2016 | bird:train.json:1924 | In which venue did Kochi Tuskers Kerala play most of their matches? | SELECT T1.Venue_Name FROM Venue AS T1 INNER JOIN Match AS T2 ON T1.Venue_Id = T2.Venue_Id INNER JOIN Team AS T3 ON T2.Team_1 = T3.Team_Id WHERE T3.Team_Name = 'Kochi Tuskers Kerala' GROUP BY T1.Venue_Name | [
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3,921 | movie_3 | bird:train.json:9360 | What is the percentage of horror film titles in English film titles? | SELECT CAST(SUM(IIF(T3.name = 'Horror', 1, 0)) AS REAL) * 100 / COUNT(T1.film_id) FROM film_category AS T1 INNER JOIN film AS T2 ON T1.film_id = T2.film_id INNER JOIN category AS T3 ON T1.category_id = T3.category_id INNER JOIN language AS T4 ON T2.language_id = T4.language_id WHERE T4.name = 'English' | [
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3,922 | financial | bird:dev.json:178 | Which kind of credit card does client number 9 possess? | SELECT T3.type FROM client AS T1 INNER JOIN disp AS T2 ON T1.client_id = T2.client_id INNER JOIN card AS T3 ON T2.disp_id = T3.disp_id WHERE T1.client_id = 9 | [
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3,924 | wine_1 | spider:train_spider.json:6541 | Give me the average prices of wines that are produced by appelations in Sonoma County. | SELECT AVG(T2.Price) FROM APPELLATIONS AS T1 JOIN WINE AS T2 ON T1.Appelation = T2.Appelation WHERE T1.County = "Sonoma" | [
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3,925 | cre_Docs_and_Epenses | spider:train_spider.json:6444 | Return the description of the budget type that has the code ORG. | SELECT budget_type_description FROM Ref_budget_codes WHERE budget_type_code = "ORG" | [
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3,926 | food_inspection_2 | bird:train.json:6208 | Which establishments did Joshua Rosa inspect? | SELECT DISTINCT T3.dba_name FROM employee AS T1 INNER JOIN inspection AS T2 ON T1.employee_id = T2.employee_id INNER JOIN establishment AS T3 ON T2.license_no = T3.license_no WHERE T1.first_name = 'Joshua' AND T1.last_name = 'Rosa' | [
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3,927 | law_episode | bird:train.json:1351 | Which episode has the highest total number of viewer votes? | SELECT T1.title FROM Episode AS T1 INNER JOIN Vote AS T2 ON T1.episode_id = T2.episode_id GROUP BY T1.title ORDER BY SUM(T1.votes) DESC LIMIT 1 | [
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3,928 | film_rank | spider:train_spider.json:4141 | How films are produced by each studio? | SELECT Studio , COUNT(*) FROM film GROUP BY Studio | [
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3,929 | wrestler | spider:train_spider.json:1863 | What are the times of elimination for wrestlers with over 50 days held? | SELECT T1.Time FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID WHERE T2.Days_held > 50 | [
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3,930 | hr_1 | spider:train_spider.json:3508 | What are the employee ids and job ids for employees who make less than the lowest earning employee with title MK_MAN? | SELECT employee_id , job_id FROM employees WHERE salary < ( SELECT min(salary) FROM employees WHERE job_id = 'MK_MAN' ) | [
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3,931 | address | bird:train.json:5161 | Give at least five alias of cities with a postal point of post office. | SELECT T1.alias FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.type = 'Post Office' LIMIT 5 | [
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3,932 | csu_1 | spider:train_spider.json:2376 | How many faculty lines are there in "San Francisco State University" in year 2004? | SELECT faculty FROM faculty AS T1 JOIN campuses AS T2 ON T1.campus = T2.id WHERE T1.year = 2004 AND T2.campus = "San Francisco State University" | [
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3,933 | cs_semester | bird:train.json:866 | Which student is more satisfied with the course Machine Learning Theory, Willie Rechert or Laughton Antonio? | SELECT T1.f_name, T1.l_name FROM student AS T1 INNER JOIN registration AS T2 ON T1.student_id = T2.student_id INNER JOIN course AS T3 ON T2.course_id = T3.course_id WHERE (T1.f_name = 'Laughton' OR T1.f_name = 'Willie') AND (T1.l_name = 'Antonio' OR T1.l_name = 'Rechert') AND T3.name = 'Machine Learning Theory' ORDER B... | [
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3,934 | wrestler | spider:train_spider.json:1876 | List the names of wrestlers that have not been eliminated. | SELECT Name FROM wrestler WHERE Wrestler_ID NOT IN (SELECT Wrestler_ID FROM elimination) | [
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"id": 2,
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{
"id": 0,
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3,935 | video_games | bird:train.json:3344 | What is the genre of the Advent Rising game? | SELECT T2.genre_name FROM game AS T1 INNER JOIN genre AS T2 ON T1.genre_id = T2.id WHERE T1.game_name = 'Advent Rising' | [
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"id": 5,
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3,936 | mondial_geo | bird:train.json:8291 | How many rivers finally flows to the sea of 459m in depth? | SELECT COUNT(*) FROM river WHERE Sea IN ( SELECT Name FROM sea WHERE Depth = 459 ) | [
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3,937 | simpson_episodes | bird:train.json:4301 | What percentage of votes are from the nominated episodes? | SELECT CAST(SUM(CASE WHEN T1.result = 'Nominee' THEN T2.votes ELSE 0 END) AS REAL) * 100 / SUM(T2.votes) FROM Award AS T1 INNER JOIN Episode AS T2 ON T1.episode_id = T2.episode_id; | [
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3,938 | card_games | bird:dev.json:416 | What percentage of cards without power are in French? | SELECT CAST(SUM(CASE WHEN T2.language = 'French' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.id) FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid WHERE T1.power IS NULL OR T1.power = '*' | [
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3,939 | authors | bird:train.json:3533 | List the authors and journal short name of the papers with "chemiluminescence" in its title and has a journal ID from 245 to 250. | SELECT T2.Name, T3.ShortName FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId INNER JOIN Journal AS T3 ON T1.JournalId = T3.Id WHERE T1.JournalId BETWEEN 245 AND 250 AND T1.Title LIKE '%chemiluminescence%' | [
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3,940 | superstore | bird:train.json:2449 | What is the order ID of the security-Tint Envelopes product ordered on June 3, 2013, in the Central region? | SELECT DISTINCT T1.`Order ID` FROM central_superstore AS T1 INNER JOIN product AS T2 ON T1.`Product ID` = T2.`Product ID` WHERE T2.`Product Name` = 'Security-Tint Envelopes' AND T1.`Order Date` = '2013-06-03' | [
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3,941 | hockey | bird:train.json:7621 | List all deceased goalies by last name. List the season where he had the most time played. | SELECT T1.playerID, T2.year, Min FROM Master AS T1 INNER JOIN Goalies AS T2 ON T2.playerID = T1.playerID WHERE T1.deathYear IS NOT NULL ORDER BY T2.Min DESC LIMIT 1 | [
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3,942 | customers_and_orders | bird:test.json:269 | How many customers do we have? | SELECT count(*) FROM Customers | [
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"id": 0,
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3,943 | talkingdata | bird:train.json:1185 | State the gender of users who use the device "-9222956879900150000". | SELECT gender FROM gender_age WHERE device_id = -9222956879900150000 | [
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3,944 | legislator | bird:train.json:4900 | Which current legislator has served for more terms, Sherrod Brown or Maria Cantwell? | SELECT CASE WHEN SUM(CASE WHEN T1.official_full_name = 'Maria Cantwell' THEN 1 ELSE 0 END) > SUM(CASE WHEN T1.official_full_name = 'Sherrod Brown' THEN 1 ELSE 0 END) THEN 'Maria Cantwell' ELSE 'Sherrod Brown' END FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide | [
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3,945 | customers_and_addresses | spider:train_spider.json:6090 | Which city is post code 255 located in? | SELECT city FROM addresses WHERE zip_postcode = 255 | [
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3,947 | movielens | bird:train.json:2264 | How many female actors acted in the movies of year 4? | SELECT COUNT(T2.actorid) FROM movies AS T1 INNER JOIN movies2actors AS T2 ON T1.movieid = T2.movieid INNER JOIN actors AS T3 ON T2.actorid = T3.actorid WHERE T3.a_gender = 'F' AND T1.year = 4 | [
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3,948 | retail_complains | bird:train.json:260 | Which detailed product did Mr Lennox Oliver Drake complain about? | SELECT DISTINCT T2.`Sub-product` FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.first = 'Lennox' AND T1.middle = 'Oliver' AND T1.last = 'Drake' AND T1.sex = 'Male' | [
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3,949 | inn_1 | spider:train_spider.json:2607 | What is the total number of rooms available in this inn? | SELECT count(*) FROM Rooms; | [
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3,950 | mondial_geo | bird:train.json:8387 | In which Country is the second highest volcanic mountain located in? Give the code of the country. | SELECT T3.Country FROM mountain AS T1 INNER JOIN geo_mountain AS T2 ON T1.Name = T2.Mountain INNER JOIN province AS T3 ON T3.Name = T2.Province ORDER BY T1.Height DESC LIMIT 1, 1 | [
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3,951 | chinook_1 | spider:train_spider.json:846 | Find the full name of the customer with the email "luisg@embraer.com.br". | SELECT FirstName , LastName FROM CUSTOMER WHERE Email = "luisg@embraer.com.br" | [
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3,952 | public_review_platform | bird:train.json:3914 | What is the correlation between the review starts and business stars? | SELECT CAST(SUM(T2.review_stars) AS REAL) / COUNT(T1.business_id) FROM Business AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id | [
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3,953 | scientist_1 | spider:train_spider.json:6508 | What are the names of scientists who have not been assigned a project? | SELECT Name FROM scientists WHERE ssn NOT IN (SELECT scientist FROM AssignedTo) | [
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3,954 | talkingdata | bird:train.json:1091 | Among the devices with event no.2 happening, how many of them are vivo devices? | SELECT COUNT(T1.device_id) FROM phone_brand_device_model2 AS T1 INNER JOIN events AS T2 ON T2.device_id = T1.device_id WHERE T1.phone_brand = 'vivo' AND T2.event_id = 2 | [
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3,955 | college_1 | spider:train_spider.json:3215 | Find the number of professors with a Ph.D. degree in each department. | SELECT count(*) , dept_code FROM professor WHERE prof_high_degree = 'Ph.D.' GROUP BY dept_code | [
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3,956 | ice_hockey_draft | bird:train.json:6931 | Among the players whose total NHL games played in their first 7 years of NHL career is no less than 500, what is the name of the player who committed the most rule violations? | SELECT T1.PlayerName FROM PlayerInfo AS T1 INNER JOIN SeasonStatus AS T2 ON T1.ELITEID = T2.ELITEID WHERE T1.sum_7yr_GP > 500 ORDER BY T2.PIM DESC LIMIT 1 | [
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3,957 | disney | bird:train.json:4649 | How many movies did Wolfgang Reitherman direct? | SELECT COUNT(name) FROM director WHERE director = 'Wolfgang Reitherman' | [
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3,958 | world_development_indicators | bird:train.json:2209 | What was the deposit interest rate in the Commonwealth of Australia in 1979 in percentage? | SELECT T1.Value FROM Indicators AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.CountryCode WHERE T2.LongName = 'Commonwealth of Australia' AND T1.IndicatorName = 'Deposit interest rate (%)' AND T1.Year = 1979 | [
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3,959 | apartment_rentals | spider:train_spider.json:1240 | Show the total number of rooms of all apartments with facility code "Gym". | SELECT sum(T2.room_count) FROM Apartment_Facilities AS T1 JOIN Apartments AS T2 ON T1.apt_id = T2.apt_id WHERE T1.facility_code = "Gym" | [
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3,960 | swimming | spider:train_spider.json:5603 | List all the event names by year from the most recent to the oldest. | SELECT name FROM event ORDER BY YEAR DESC | [
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},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"... | [
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
3,962 | works_cycles | bird:train.json:7142 | What's Emma H Harris's Business Entity ID number? | SELECT BusinessEntityID FROM Person WHERE FirstName = 'Emma' AND LastName = 'Harris' | [
"What",
"'s",
"Emma",
"H",
"Harris",
"'s",
"Business",
"Entity",
"ID",
"number",
"?"
] | [
{
"id": 1,
"type": "column",
"value": "businessentityid"
},
{
"id": 2,
"type": "column",
"value": "firstname"
},
{
"id": 4,
"type": "column",
"value": "lastname"
},
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 5,
"type": "value",
... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
... | [
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O"
] |
3,963 | social_media | bird:train.json:833 | Calculate the average number of male users who posted tweets in a week. | SELECT COUNT(DISTINCT T1.TweetID) / COUNT(DISTINCT T1.UserID) / 7 AS avg FROM twitter AS T1 INNER JOIN user AS T2 ON T1.UserID = T2.UserID WHERE T2.Gender = 'Male' AND T1.Day BETWEEN 1 AND 31 | [
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"male",
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"tweets",
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"."
] | [
{
"id": 0,
"type": "table",
"value": "twitter"
},
{
"id": 8,
"type": "column",
"value": "tweetid"
},
{
"id": 2,
"type": "column",
"value": "userid"
},
{
"id": 3,
"type": "column",
"value": "gender"
},
{
"id": 4,
"type": "value",
"value": "M... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": ... | [
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"O",
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"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
3,964 | customers_card_transactions | spider:train_spider.json:678 | How many accounts are there for each customer id? | SELECT customer_id , count(*) FROM Accounts GROUP BY customer_id | [
"How",
"many",
"accounts",
"are",
"there",
"for",
"each",
"customer",
"i",
"d",
"?"
] | [
{
"id": 1,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "table",
"value": "accounts"
}
] | [
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
7,
8,
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
... | [
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
3,965 | farm | spider:train_spider.json:46 | List the most common type of Status across cities. | SELECT Status FROM city GROUP BY Status ORDER BY COUNT(*) DESC LIMIT 1 | [
"List",
"the",
"most",
"common",
"type",
"of",
"Status",
"across",
"cities",
"."
] | [
{
"id": 1,
"type": "column",
"value": "status"
},
{
"id": 0,
"type": "table",
"value": "city"
}
] | [
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"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",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
3,966 | soccer_2 | spider:train_spider.json:5021 | What are the names of all tryout participants who are from the largest college? | SELECT T2.pName FROM tryout AS T1 JOIN player AS T2 ON T1.pID = T2.pID WHERE T1.cName = (SELECT cName FROM college ORDER BY enr DESC LIMIT 1) | [
"What",
"are",
"the",
"names",
"of",
"all",
"tryout",
"participants",
"who",
"are",
"from",
"the",
"largest",
"college",
"?"
] | [
{
"id": 5,
"type": "table",
"value": "college"
},
{
"id": 1,
"type": "table",
"value": "tryout"
},
{
"id": 2,
"type": "table",
"value": "player"
},
{
"id": 0,
"type": "column",
"value": "pname"
},
{
"id": 3,
"type": "column",
"value": "cnam... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": ... | [
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
3,967 | book_review | bird:test.json:593 | How many books are there? | SELECT count(*) FROM book | [
"How",
"many",
"books",
"are",
"there",
"?"
] | [
{
"id": 0,
"type": "table",
"value": "book"
}
] | [
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
... | [
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
3,968 | thrombosis_prediction | bird:dev.json:1152 | What is the ratio of outpatient to inpatient followed up treatment among all the 'SLE' diagnosed patient? | SELECT SUM(CASE WHEN Admission = '+' THEN 1.0 ELSE 0 END) / SUM(CASE WHEN Admission = '-' THEN 1 ELSE 0 END) FROM Patient WHERE Diagnosis = 'SLE' | [
"What",
"is",
"the",
"ratio",
"of",
"outpatient",
"to",
"inpatient",
"followed",
"up",
"treatment",
"among",
"all",
"the",
"'",
"SLE",
"'",
"diagnosed",
"patient",
"?"
] | [
{
"id": 1,
"type": "column",
"value": "diagnosis"
},
{
"id": 6,
"type": "column",
"value": "admission"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 2,
"type": "value",
"value": "SLE"
},
{
"id": 4,
"type": "value",
"value": "... | [
{
"entity_id": 0,
"token_idxs": [
18
]
},
{
"entity_id": 1,
"token_idxs": [
17
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
... | [
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
3,969 | twitter_1 | spider:train_spider.json:287 | Find the names of users who have more than one tweet. | SELECT T1.name FROM user_profiles AS T1 JOIN tweets AS T2 ON T1.uid = T2.uid GROUP BY T2.uid HAVING count(*) > 1 | [
"Find",
"the",
"names",
"of",
"users",
"who",
"have",
"more",
"than",
"one",
"tweet",
"."
] | [
{
"id": 2,
"type": "table",
"value": "user_profiles"
},
{
"id": 3,
"type": "table",
"value": "tweets"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 0,
"type": "column",
"value": "uid"
},
{
"id": 4,
"type": "value",
"value": "1"... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs":... | [
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
3,970 | cs_semester | bird:train.json:898 | How many students does Ogdon Zywicki advise? | SELECT COUNT(T1.student_id) FROM RA AS T1 INNER JOIN prof AS T2 ON T1.prof_id = T2.prof_id WHERE T2.first_name = 'Ogdon' AND T2.last_name = 'Zywicki' | [
"How",
"many",
"students",
"does",
"Ogdon",
"Zywicki",
"advise",
"?"
] | [
{
"id": 2,
"type": "column",
"value": "student_id"
},
{
"id": 4,
"type": "column",
"value": "first_name"
},
{
"id": 6,
"type": "column",
"value": "last_name"
},
{
"id": 3,
"type": "column",
"value": "prof_id"
},
{
"id": 7,
"type": "value",
... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
4
... | [
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O"
] |
3,971 | movie_1 | spider:train_spider.json:2516 | What are the ids of the movies that are not reviewed by Brittany Harris. | SELECT mID FROM Rating EXCEPT SELECT T1.mID FROM Rating AS T1 JOIN Reviewer AS T2 ON T1.rID = T2.rID WHERE T2.name = "Brittany Harris" | [
"What",
"are",
"the",
"ids",
"of",
"the",
"movies",
"that",
"are",
"not",
"reviewed",
"by",
"Brittany",
"Harris",
"."
] | [
{
"id": 4,
"type": "column",
"value": "Brittany Harris"
},
{
"id": 2,
"type": "table",
"value": "reviewer"
},
{
"id": 0,
"type": "table",
"value": "rating"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "column",
"val... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12,
13
]
},
{
"entity_id": 5,
"t... | [
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
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