Database: college_completion
Question: What is the institution's name of american students within the number of degree-seeking students in the cohort that ranges from 1 to 3?
Evidence: institution's name refers to chronname; american refers to race = 'Ai'; number of degree-seeking students in the cohort refers to grad_cohort; grad_cohort < = 3;
SQL: SELECT DISTINCT T1.chronname FROM institution_details AS T1 INNER JOIN institution_grads AS T2 ON T2.unitid = T1.unitid WHERE T2.grad_cohort BETWEEN 1 AND 3 AND T2.race = 'Ai'

Database: ice_hockey_draft
Question: Please list the names of all the players with a height of over 6'2" inches.
Evidence: name of the players refers to PlayerName; height of over 6'2" inches refers to height_in_inch > '6''2"' ;
SQL: SELECT DISTINCT T1.PlayerName FROM PlayerInfo AS T1 INNER JOIN height_info AS T2 ON T1.height = T2.height_id WHERE T2.height_in_inch > '6''2"'

Database: law_episode
Question: What is the title of the episode with the highest number of keywords?
Evidence: the highest number of keywords refers to max(count(keyword))
SQL: SELECT T1.title FROM Episode AS T1 INNER JOIN Keyword AS T2 ON T1.episode_id = T2.episode_id GROUP BY T1.episode_id ORDER BY COUNT(T2.keyword) DESC LIMIT 1

Database: image_and_language
Question: How many images have a total of 10 attribute classes?
Evidence: images refer to IMG_ID; total of 10 attribute classes refers to COUNT(OBJ_CLASS_ID) = 10;
SQL: SELECT COUNT(IMG_ID) FROM IMG_OBJ WHERE OBJ_CLASS_ID = 10

Database: soccer_2016
Question: What is the percentage of all right-handed batting players among all the other players?
Evidence: right-handed batting refers to Batting_hand = 'Right-hand bat'; percentage = divide(count(Player_Id where Batting_hand = 'Right-hand bat'), count(Player_Id)) * 100%
SQL: SELECT CAST(SUM(CASE WHEN T1.Batting_hand = 'Right-hand bat' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.Player_Id) FROM Batting_Style AS T1 INNER JOIN Player AS T2 ON T2.Batting_hand = T1.Batting_Id

Database: address
Question: In cities that do not implement daylight savings, what is the total number of cities?
Evidence: do not implement daylight savings refers to daylight_savings = 'No';
SQL: SELECT COUNT(T1.area_code) FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.daylight_savings = 'No'

Database: synthea
Question: Who is the patient involved in the care plan with code 311791003?
SQL: SELECT T2.first, T2.last FROM careplans AS T1 INNER JOIN patients AS T2 ON T1.PATIENT = T2.patient WHERE T1.CODE = 315043002

Database: world_development_indicators
Question: How many footnotes did Aruba got on different series code in the year 2002?
Evidence: Aruba is the name of country where ShortName = 'Aruba'
SQL: SELECT COUNT(T2.SeriesCode) FROM Country AS T1 INNER JOIN FootNotes AS T2 ON T1.CountryCode = T2.Countrycode WHERE T1.ShortName = 'Aruba' AND T2.Year = 'YR2002'

Database: chicago_crime
Question: How many severe crime incidents were reported at coordinate 41.64820151, -87.54430496?
Evidence: coordinates refers to latitude, longitude; severe crime refers to index_code = 'I'
SQL: SELECT SUM(CASE WHEN T1.longitude = '-87.54430496' THEN 1 ELSE 0 END) FROM Crime AS T1 INNER JOIN IUCR AS T2 ON T1.report_no = T2.iucr_no WHERE T2.index_code = 'I' AND T1.latitude = '41.64820251'

Database: retail_world
Question: List down the quantity per unit for products of Tokyo Traders.
Evidence: "Tokyo Traders" is the CompanyName
SQL: SELECT T1.QuantityPerUnit FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T2.CompanyName = 'Tokyo Traders'

Database: university
Question: Provide the country name of universities with the number of students greater than 98% of the average student population of all universities in 2013.
Evidence: number of students greater than 98% of the average student population of all universities refers to num_students >  MULTPLY(num_students, 0.98); in 2013 refers to year = 2013
SQL: SELECT DISTINCT T3.country_name FROM university AS T1 INNER JOIN university_year AS T2 ON T1.id = T2.university_id INNER JOIN country AS T3 ON T3.id = T1.country_id WHERE T2.year = 2013 AND T2.num_students * 100 > ( SELECT AVG(num_students) FROM university_year ) * 98

Database: legislator
Question: Among all the female current legislators, how many of them have served for more than 4 terms?
Evidence: female refers to gender_bio = 'F'; served for more than 4 terms refers to COUNT(bioguide > 4)
SQL: SELECT COUNT(CID) FROM ( SELECT T1.bioguide_id AS CID FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T1.gender_bio = 'F' GROUP BY T2.bioguide HAVING COUNT(T2.bioguide) > 4 )

Database: movie
Question: Please list the names of the actors who played a role in the movie Batman.
Evidence: movie Batman refers to title = 'Batman'
SQL: SELECT T3.Name FROM movie AS T1 INNER JOIN characters AS T2 ON T1.MovieID = T2.MovieID INNER JOIN actor AS T3 ON T3.ActorID = T2.ActorID WHERE T1.Title = 'Batman'

Database: beer_factory
Question: What is the container type, brand name and star rating for root beer ID 10054?
Evidence: FALSE;
SQL: SELECT T4.ContainerType, T3.BrandName, T1.StarRating FROM rootbeerreview AS T1 INNER JOIN `transaction` AS T2 ON T1.CustomerID = T2.CustomerID INNER JOIN rootbeerbrand AS T3 ON T1.BrandID = T3.BrandID INNER JOIN rootbeer AS T4 ON T2.RootBeerID = T4.RootBeerID WHERE T2.RootBeerID = 100054

Database: movies_4
Question: Provide the production companies of the movie that has over 35% average running time per movie in 2016.
Evidence: production companies refers to company_name; in 2016 refers to release_date LIKE '2016%'; over 35% average running time per movie refers to divide(subtract(runtime, AVG(runtime)), AVG(runtime)) * 100 as percentage > 35
SQL: SELECT T.company_name FROM ( SELECT DISTINCT T3.company_name, T1.runtime FROM movie AS T1 INNER JOIN movie_company AS T2 ON T1.movie_id = T2.movie_id INNER JOIN production_company AS T3 ON T3.company_id = T2.company_id WHERE T1.release_date LIKE '2016%' ) T WHERE T.runtime * 100 > (0.35 * ( SELECT AVG(T1.runtime) FROM movie AS T1 INNER JOIN movie_company AS T2 ON T1.movie_id = T2.movie_id INNER JOIN production_company AS T3 ON T3.company_id = T2.company_id WHERE T1.release_date LIKE '2016%' ) + ( SELECT AVG(T1.runtime) FROM movie AS T1 INNER JOIN movie_company AS T2 ON T1.movie_id = T2.movie_id INNER JOIN production_company AS T3 ON T3.company_id = T2.company_id WHERE T1.release_date LIKE '2016%' )) * 100

Database: books
Question: What is the title of the first book that was published in 1900?
Evidence: published in 1900 refers to publication_date LIKE '1900%'; first book refers to Min(publication_date)
SQL: SELECT title FROM book WHERE STRFTIME('%Y', publication_date) = '1900' ORDER BY publication_date LIMIT 1

Database: movies_4
Question: List down five movie titles that were released before 2000.
Evidence: released before 2000 refers to release_date < '2000-01-01'
SQL: SELECT title FROM movie WHERE CAST(STRFTIME('%Y', release_date) AS INT) < 2000 LIMIT 5

Database: public_review_platform
Question: List the active business ID and its stars of the businesses fall under the category of Fashion.
Evidence: active business refers to active = 'true'; category of Fashion refers to category = 'Fashion'
SQL: SELECT T1.business_id, T1.stars FROM Business AS T1 INNER JOIN Business_Categories ON T1.business_id = Business_Categories.business_id INNER JOIN Categories AS T3 ON Business_Categories.category_id = T3.category_id WHERE T1.active LIKE 'TRUE' AND T3.category_name LIKE 'Fashion'

Database: talkingdata
Question: What are the labels' IDs of online shopping and online malls categories?
SQL: SELECT label_id FROM label_categories WHERE category IN ('online shopping', 'online malls')