Database: movielens
Question: Among the best actors, how many of them got a rating of 5 to the movies they starred?
SQL: SELECT COUNT(T1.actorid) FROM actors AS T1 INNER JOIN movies2actors AS T2 ON T1.actorid = T2.actorid INNER JOIN u2base AS T3 ON T2.movieid = T3.movieid WHERE T1.a_quality = 5 AND T3.rating = 5

Database: disney
Question: List the movie titles with the voice actor Jeff Bennet
Evidence: Jeff Bennett refers to voice-actor = 'Jeff Bennett';
SQL: SELECT movie FROM `voice-actors` WHERE 'voice-actor' = 'Jeff Bennett'

Database: soccer_2016
Question: Provide the complete name of the venue, city and country where the last match was held.
Evidence: name of the venue, city and country refers to Venue_Name and City_Name and Country_Name; last match refers to max(Match_Date)
SQL: SELECT T1.Venue_Name, T2.City_Name, T3.Country_Name FROM Venue AS T1 INNER JOIN City AS T2 ON T1.City_Id = T2.City_Id INNER JOIN Country AS T3 ON T2.Country_Id = T3.Country_Id INNER JOIN Match AS T4 ON T1.Venue_Id = T4.Venue_Id ORDER BY T4.Match_Date DESC LIMIT 1

Database: authors
Question: What is the url of the journal in which the paper "Area Effects in Cepaea" was published?
Evidence: url refers to HomePage; 'Area Effects in Cepaea' is the Title of paper
SQL: SELECT T1.HomePage FROM Journal AS T1 INNER JOIN Paper AS T2 ON T1.Id = T2.JournalId WHERE T2.Title = 'Area Effects in Cepaea'

Database: coinmarketcap
Question: Which crytocurrency was not opened on 2013/5/3?
Evidence: not opened refers to open IS NULL; on 2013/5/3 refers to date = '2013-05-03'
SQL: SELECT T1.name FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T2.date = '2013-05-03' AND T2.open IS NULL

Database: public_review_platform
Question: Among the active businesses located at Mesa, AZ, list the category and attributes of business with a low review count.
Evidence: active business refers to active = 'true': 'Mesa' is the name of city; 'AZ' is the state; low review count refers to review_count = 'Low'; category refers to category_name
SQL: SELECT T3.category_name FROM Business AS T1 INNER JOIN Business_Categories AS T2 ON T1.business_id = T2.business_id INNER JOIN Categories AS T3 ON T2.category_id = T3.category_id WHERE T1.review_count = 'Low' AND T1.city = 'Mesa' AND T1.active = 'true' AND T1.state = 'AZ'

Database: cs_semester
Question: Name the students with above-average capability.
Evidence: name of the students = f_name, l_name; above average-capability refers to capability > AVG(capability);
SQL: SELECT T1.f_name, T1.l_name FROM student AS T1 INNER JOIN RA AS T2 ON T1.student_id = T2.student_id WHERE T2.capability > ( SELECT AVG(capability) FROM RA )

Database: authors
Question: What is the title and author ID of paper with conference ID less than 100 in year 2006?
Evidence: conference ID less than 100 refers to ConferenceId < 100; in year 2006 refers to Year = 2006
SQL: SELECT DISTINCT T1.Title, T2.AuthorId FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T1.Year = 2006 AND T1.ConferenceId < 100

Database: sales
Question: Give the product's name brought by Aaron Alexander.
SQL: SELECT DISTINCT T1.Name FROM Products AS T1 INNER JOIN Sales AS T2 ON T1.ProductID = T2.ProductID INNER JOIN Customers AS T3 ON T2.CustomerID = T3.CustomerID WHERE T3.FirstName = 'Aaron' AND T3.LastName = 'Alexander'

Database: soccer_2016
Question: Count the matches that were won by wickets in all season.
Evidence: won by wickets refers to Win_type = 'wickets';
SQL: SELECT COUNT(T1.Match_Id) FROM Match AS T1 INNER JOIN Win_By AS T2 ON T1.Win_Type = T2.Win_Id WHERE T2.Win_type = 'wickets'

Database: talkingdata
Question: How many app users belong to label ID of "48"?
SQL: SELECT COUNT(app_id) FROM app_labels WHERE label_id = 48

Database: public_review_platform
Question: List all the businesses that closed at 8PM.
Evidence: closed at 8PM refers to closing_time = '8PM';
SQL: SELECT DISTINCT business_id FROM Business_Hours WHERE closing_time = '8PM'

Database: social_media
Question: How many tweets in French were posted from Australia?
Evidence: "French" is the language and refers to Lang = 'fr'; 'Australia' is the Country
SQL: SELECT COUNT(DISTINCT T1.TweetID) FROM twitter AS T1 INNER JOIN location AS T2 ON T1.LocationID = T2.LocationID WHERE T1.Lang = 'fr' AND T2.Country = 'Australia'

Database: social_media
Question: Which country's tweets collected the most likes?
Evidence: country collected the most likes refers to Country where Max(Sum(Likes))
SQL: SELECT T.Country FROM ( SELECT T2.Country, SUM(T1.Likes) AS num FROM twitter AS T1 INNER JOIN location AS T2 ON T1.LocationID = T2.LocationID GROUP BY T2.Country ) T ORDER BY T.num DESC LIMIT 1

Database: superstore
Question: Who is the customer who purchased the largest total cost of products in a single order?
Evidence: largest total cost refers to MAX(SUTRACT(MULTIPLY(DIVIDE(Sales, SUTRACT(1, discount)), Quantity), Profit))
SQL: SELECT T2.`Customer Name` FROM east_superstore AS T1 INNER JOIN people AS T2 ON T1.`Customer ID` = T2.`Customer ID` GROUP BY T1.`Order ID`, T2.`Customer Name` ORDER BY SUM((T1.Sales / (1 - T1.Discount)) * T1.Quantity - T1.Profit) DESC LIMIT 1

Database: books
Question: Which country does the customer with the email "rturbitt2@geocities.jp" from?
Evidence: "rturbitt2@geocities.jp" is the email of customer; country refers to country_name
SQL: SELECT T4.country_name FROM customer AS T1 INNER JOIN customer_address AS T2 ON T1.customer_id = T2.customer_id INNER JOIN address AS T3 ON T3.address_id = T2.address_id INNER JOIN country AS T4 ON T4.country_id = T3.country_id WHERE T1.email = 'rturbitT2@geocities.jp'

Database: movie_platform
Question: Please list the names of the top three movies in the number comments related to the critic made by the user rating the movie.
Evidence: number of comments related to the critic made by the user rating the movie refers to critic_comments; top movie refers to Max(critic_comments);
SQL: SELECT T2.movie_title FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id ORDER BY T1.critic_comments DESC LIMIT 3

Database: social_media
Question: What is the gender of the user who has posted the tweet that got the most likes?
Evidence: tweet got the most likes refers to Max(Likes)
SQL: SELECT T2.Gender FROM twitter AS T1 INNER JOIN user AS T2 ON T1.UserID = T2.UserID ORDER BY T1.Likes DESC LIMIT 1

Database: chicago_crime
Question: How many of the crimes that happened in the street have FBI title "Homicide 1st & 2nd Degree"?
Evidence: in the street refers to location_description = 'STREET'
SQL: SELECT SUM(CASE WHEN T2.location_description = 'STREET' THEN 1 ELSE 0 END) FROM FBI_Code AS T1 INNER JOIN Crime AS T2 ON T2.fbi_code_no = T1.fbi_code_no WHERE T1.title = 'Homicide 1st & 2nd Degree'

Database: simpson_episodes
Question: How many crew members who were born in the USA were nominated for the Outstanding Animated Program (For Programming Less Than One Hour) award in 2009?
Evidence: born in USA refers to birth_country = 'USA'; were nominated refers to result = 'Nominee'; 'Outstanding Animated Program (For Programming Less Than One Hour)' is the award; in 2009 refers to year = 2009
SQL: SELECT COUNT(*) FROM Person AS T1 INNER JOIN Award AS T2 ON T1.name = T2.person WHERE T1.birth_country = 'USA' AND T2.result = 'Nominee' AND T2.award = 'Outstanding Animated Program (For Programming Less Than One Hour)' AND T2.year = 2009;

Database: movielens
Question: What's different average revenue status for director who directed the movie that got the most 1 ratings?
SQL: SELECT DISTINCT T1.avg_revenue FROM directors AS T1 INNER JOIN movies2directors AS T2 ON T1.directorid = T2.directorid WHERE T1.d_quality = 5