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3,972 | beer_factory | bird:train.json:5271 | How many transactions were paid through MasterCard in 2014? | SELECT COUNT(TransactionID) FROM `transaction` WHERE CreditCardType = 'MasterCard' AND TransactionDate LIKE '2014%' | [
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3,973 | movies_4 | bird:train.json:532 | List the film with the highest budget in each genre. | SELECT T3.genre_name, MAX(T1.budget) FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T2.genre_id = T3.genre_id GROUP BY T3.genre_name | [
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3,974 | superstore | bird:train.json:2417 | Among the orders in Central superstore, which art product were ordered the most? | SELECT T2.`Product Name` FROM central_superstore AS T1 INNER JOIN product AS T2 ON T1.`Product ID` = T2.`Product ID` WHERE T2.`Sub-Category` = 'Art' GROUP BY T2.`Product Name` ORDER BY COUNT(T2.`Product ID`) DESC LIMIT 1 | [
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3,975 | hr_1 | spider:train_spider.json:3457 | display job ID for those jobs that were done by two or more for more than 300 days. | SELECT job_id FROM job_history WHERE end_date - start_date > 300 GROUP BY job_id HAVING COUNT(*) >= 2 | [
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3,976 | disney | bird:train.json:4676 | What are the total grosses for the movies with Jim Cummings as the voice actor? | SELECT T2.movie_title FROM `voice-actors` AS T1 INNER JOIN movies_total_gross AS T2 ON T2.movie_title = T1.movie WHERE T1.`voice-actor` = 'Jim Cummings' ORDER BY CAST(REPLACE(trim(T2.total_gross, '$'), ',', '') AS REAL) DESC LIMIT 1 | [
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3,977 | professional_basketball | bird:train.json:2921 | Player from which team has the highest point per minute in NBA from 1991 to 2000? | SELECT tmID FROM players_teams WHERE year BETWEEN 1991 AND 2000 ORDER BY CAST(points AS REAL) / minutes DESC LIMIT 1 | [
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3,978 | baseball_1 | spider:train_spider.json:3653 | How many players born in USA are right-handed batters? That is, have the batter value 'R'. | SELECT count(*) FROM player WHERE birth_country = 'USA' AND bats = 'R'; | [
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3,979 | movielens | bird:train.json:2249 | List the genres of the movies which actor id 851 is the star. | SELECT T2.genre FROM movies2actors AS T1 INNER JOIN movies2directors AS T2 ON T1.movieid = T2.movieid INNER JOIN actors AS T3 ON T1.actorid = T3.actorid WHERE T3.actorid = 851 | [
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3,980 | region_building | bird:test.json:322 | Among the buildings not completed in 1980, what is the maximum number of stories? | SELECT max(Number_of_Stories) FROM building WHERE Completed_Year != "1980" | [
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3,982 | video_games | bird:train.json:3473 | What are the game IDs of the games published by Bethesda Softworks? | SELECT T1.game_id FROM game_publisher AS T1 INNER JOIN publisher AS T2 ON T1.publisher_id = T2.id WHERE T2.publisher_name = 'Bethesda Softworks' | [
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3,983 | toxicology | bird:dev.json:198 | On average how many carcinogenic molecules are single bonded? | SELECT AVG(single_bond_count) FROM (SELECT T3.molecule_id, COUNT(T1.bond_type) AS single_bond_count FROM bond AS T1 INNER JOIN atom AS T2 ON T1.molecule_id = T2.molecule_id INNER JOIN molecule AS T3 ON T3.molecule_id = T2.molecule_id WHERE T1.bond_type = '-' AND T3.label = '+' GROUP BY T3.molecule_id) AS subquery | [
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3,984 | superhero | bird:dev.json:766 | What is the hero's full name with the highest attribute in strength? | SELECT T1.full_name FROM superhero AS T1 INNER JOIN hero_attribute AS T2 ON T1.id = T2.hero_id INNER JOIN attribute AS T3 ON T2.attribute_id = T3.id WHERE T3.attribute_name = 'Strength' ORDER BY T2.attribute_value DESC LIMIT 1 | [
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3,985 | store_1 | spider:train_spider.json:559 | List total amount of invoice from Chicago, IL. | SELECT sum(total) FROM invoices WHERE billing_city = "Chicago" AND billing_state = "IL"; | [
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3,986 | company_office | spider:train_spider.json:4580 | How many companies are in either "Banking" industry or "Conglomerate" industry? | SELECT count(*) FROM Companies WHERE Industry = "Banking" OR Industry = "Conglomerate" | [
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3,987 | restaurant | bird:train.json:1718 | What is the name of the least popular Indian restaurant on Shattuck Avenue in Berkeley? | SELECT T1.id_restaurant FROM generalinfo AS T1 INNER JOIN location AS T2 ON T1.id_restaurant = T2.id_restaurant WHERE T1.city = 'berkeley' AND T2.street_name = 'shattuck ave' AND T1.food_type = 'Indian restaurant' ORDER BY T1.review LIMIT 1 | [
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3,988 | thrombosis_prediction | bird:dev.json:1298 | Among the patients whose total cholesterol is within the normal range, how many of them have a P pattern observed in the sheet of ANA examination? | SELECT COUNT(T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID INNER JOIN Examination AS T3 ON T1.ID = T3.ID WHERE T3.`ANA Pattern` = 'P' AND T2.`T-CHO` < 250 | [
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3,989 | language_corpus | bird:train.json:5802 | How many times does the biwords "que gregorio" appear in the language? | SELECT occurrences FROM biwords WHERE w1st = ( SELECT wid FROM words WHERE word = 'que' ) AND w2nd = ( SELECT wid FROM words WHERE word = 'gregorio' ) | [
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3,990 | simpson_episodes | bird:train.json:4192 | What is the title of episode that has a keyword of 'riot' and 'cake'? | SELECT DISTINCT T1.title FROM Episode AS T1 INNER JOIN Keyword AS T2 ON T1.episode_id = T2.episode_id WHERE T2.keyword IN ('riot', 'cake'); | [
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3,991 | superstore | bird:train.json:2459 | List the customer's name from the South region with a standard class ship mode and sales greater than the 88% of the average sales of all orders. | SELECT DISTINCT T2.`Customer Name` FROM south_superstore AS T1 INNER JOIN people AS T2 ON T1.`Customer ID` = T2.`Customer ID` WHERE T2.Region = 'South' AND T1.`Ship Mode` = 'Standard Class' AND 100 * T1.Sales / ( SELECT AVG(Sales) FROM south_superstore ) > 88 | [
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3,992 | beer_factory | bird:train.json:5293 | On average how many caffeinated root beers are sold a day? | SELECT CAST(COUNT(T2.RootBeerID) AS REAL) / COUNT(DISTINCT T2.PurchaseDate) FROM rootbeerbrand AS T1 INNER JOIN rootbeer AS T2 ON T1.BrandID = T2.BrandID INNER JOIN `transaction` AS T3 ON T2.RootBeerID = T3.RootBeerID WHERE T1.Caffeinated = 'TRUE' | [
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3,993 | retails | bird:train.json:6793 | How many different clerks have served the customer with the address uFTe2u518et8Q8UC? | SELECT COUNT(T1.o_clerk) FROM orders AS T1 INNER JOIN customer AS T2 ON T1.o_custkey = T2.c_custkey WHERE T2.c_address = 'uFTe2u518et8Q8UC' | [
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3,994 | allergy_1 | spider:train_spider.json:484 | What is the minimum, mean, and maximum age across all students? | SELECT min(age) , avg(age) , max(age) FROM Student | [
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3,995 | movies_4 | bird:train.json:429 | Provide the most used keyword in the movies. | SELECT T1.keyword_name FROM keyword AS T1 INNER JOIN movie_keywords AS T2 ON T1.keyword_id = T2.keyword_id GROUP BY T1.keyword_name ORDER BY COUNT(T1.keyword_name) DESC LIMIT 1 | [
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3,996 | shakespeare | bird:train.json:2966 | What is the average number of characters in all the works of Shakespeare? | SELECT SUM(DISTINCT T4.id) / COUNT(T1.id) 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 | [
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3,998 | vehicle_rent | bird:test.json:396 | Count the number of vehicles. | SELECT count(*) FROM vehicles | [
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3,999 | world_development_indicators | bird:train.json:2115 | Enumerate the footnote narratives of The Bahamas under the series code SH.DTH.IMRT in the year 1984. | SELECT DISTINCT T1.Description FROM FootNotes AS T1 INNER JOIN Country AS T2 ON T1.Countrycode = T2.CountryCode WHERE T1.Year = 'YR1984' AND T2.ShortName = 'The Bahamas' AND T1.Seriescode = 'SH.DTH.IMRT' | [
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4,000 | ship_1 | spider:train_spider.json:6231 | Return the rank for which there are the fewest captains. | SELECT rank FROM captain GROUP BY rank ORDER BY count(*) DESC LIMIT 1 | [
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4,001 | financial | bird:dev.json:182 | How many male customers who were born between 1974 and 1976 have made a payment on their home in excess of $4000? | SELECT COUNT(T1.account_id) FROM trans AS T1 INNER JOIN account AS T2 ON T1.account_id = T2.account_id INNER JOIN disp AS T4 ON T2.account_id = T4.account_id INNER JOIN client AS T3 ON T4.client_id = T3.client_id WHERE STRFTIME('%Y', T3.birth_date) BETWEEN '1974' AND '1976' AND T3.gender = 'M' AND T1.amount > 4000 AND ... | [
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4,003 | machine_repair | spider:train_spider.json:2236 | What are the names of the technicians by ascending order of age? | SELECT Name FROM technician ORDER BY Age ASC | [
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4,004 | formula_1 | bird:dev.json:1011 | Which top 20 driver created the shortest lap time ever record in a Formula_1 race? Please give them full names. | WITH lap_times_in_seconds AS (SELECT driverId, (CASE WHEN SUBSTR(time, 1, INSTR(time, ':') - 1) <> '' THEN CAST(SUBSTR(time, 1, INSTR(time, ':') - 1) AS REAL) * 60 ELSE 0 END + CASE WHEN SUBSTR(time, INSTR(time, ':') + 1, INSTR(time, '.') - INSTR(time, ':') - 1) <> '' THEN CAST(SUBSTR(time, INSTR(time, ':') + 1, INSTR(... | [
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4,005 | warehouse_1 | bird:test.json:1729 | Find the code and content of all boxes whose value is higher than the value of all boxes with Scissors as content. | SELECT code , CONTENTS FROM boxes WHERE value > (SELECT max(value) FROM boxes WHERE CONTENTS = 'Scissors') | [
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4,006 | thrombosis_prediction | bird:dev.json:1160 | What is the percentage of female patient had total protein not within the normal range? | SELECT CAST(SUM(CASE WHEN T1.SEX = 'F' AND (T2.TP < 6.0 OR T2.TP > 8.5) THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T1.SEX = 'F' | [
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4,007 | chinook_1 | spider:train_spider.json:842 | Count the number of tracks that are part of the rock genre. | SELECT COUNT(*) FROM GENRE AS T1 JOIN TRACK AS T2 ON T1.GenreId = T2.GenreId WHERE T1.Name = "Rock" | [
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4,008 | video_games | bird:train.json:3338 | How many sales does game platform id 3871 make in Europe? | SELECT T2.num_sales * 100000 FROM region AS T1 INNER JOIN region_sales AS T2 ON T1.id = T2.region_id WHERE T1.region_name = 'Europe' AND T2.game_platform_id = 3871 | [
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4,009 | superhero | bird:dev.json:763 | Indicate the attribute value of superhero Abomination. | SELECT T2.attribute_value FROM superhero AS T1 INNER JOIN hero_attribute AS T2 ON T1.id = T2.hero_id WHERE T1.superhero_name = 'Abomination' | [
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4,013 | college_1 | spider:train_spider.json:3318 | What are the names of all students who took a class and the corresponding course descriptions? | SELECT T1.stu_fname , T1.stu_lname , T4.crs_description FROM student AS T1 JOIN enroll AS T2 ON T1.stu_num = T2.stu_num JOIN CLASS AS T3 ON T2.class_code = T3.class_code JOIN course AS T4 ON T3.crs_code = T4.crs_code | [
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4,014 | headphone_store | bird:test.json:939 | Which earpads never use plastic construction? | SELECT earpads FROM headphone EXCEPT SELECT earpads FROM headphone WHERE construction = 'Plastic' | [
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4,015 | match_season | spider:train_spider.json:1101 | What are the names of all colleges that have two or more players? | SELECT College FROM match_season GROUP BY College HAVING count(*) >= 2 | [
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4,016 | retail_world | bird:train.json:6621 | What are the the total number of territory in each region? | SELECT COUNT(TerritoryDescription) FROM Territories WHERE RegionID IN (1, 2, 3, 4) GROUP BY RegionID | [
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4,017 | airline | bird:train.json:5853 | What is the description of the airline code 19049? | SELECT Description FROM `Air Carriers` WHERE Code = 19049 | [
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4,018 | formula_1 | bird:dev.json:948 | What are the maximum points of British constructors? | SELECT MAX(T1.points) FROM constructorStandings AS T1 INNER JOIN constructors AS T2 on T1.constructorId = T2.constructorId WHERE T2.nationality = 'British' | [
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4,019 | game_1 | spider:train_spider.json:5970 | How many video games do you have? | SELECT count(*) FROM Video_games | [
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4,020 | university | bird:train.json:8114 | Calculate the average score of university ID 79 between year 2013 to 2015. | SELECT AVG(score) FROM university_ranking_year WHERE year BETWEEN 2013 AND 2015 AND university_id = 79 | [
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4,021 | college_completion | bird:train.json:3691 | In 2012, how many Asian female graduates were seeking another type of degree or certificate at the 4-year institution at University of Alaska at Anchorage? | SELECT COUNT(*) FROM institution_details AS T1 INNER JOIN institution_grads AS T2 ON T1.unitid = T2.unitid WHERE T2.gender = 'F' AND T2.race = 'A' AND T1.chronname = 'University of Alaska at Anchorage' AND T2.cohort = '4y other' | [
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4,022 | coffee_shop | spider:train_spider.json:802 | Find the address and staff number of the shops that do not have any happy hour. | SELECT address , num_of_staff FROM shop WHERE shop_id NOT IN (SELECT shop_id FROM happy_hour) | [
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4,023 | language_corpus | bird:train.json:5767 | How many word that has number of different words equal to 3? | SELECT COUNT(T2.wid) FROM pages AS T1 INNER JOIN pages_words AS T2 ON T1.pid = T2.pid WHERE T1.words = 3 | [
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4,024 | chicago_crime | bird:train.json:8757 | How many incidents have the general description of "ASSAULT" in the IUCR classification? | SELECT COUNT(*) FROM IUCR WHERE primary_description = 'ASSAULT' | [
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4,026 | student_loan | bird:train.json:4395 | Name all disabled students that are enrolled in SMC. | SELECT T2.name FROM enrolled AS T1 INNER JOIN disabled AS T2 ON T1.`name` = T2.`name` WHERE T1.school = 'smc' | [
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4,027 | food_inspection_2 | bird:train.json:6205 | Did license number 1222441 pass the inspection and what is the zip code number of it? | SELECT DISTINCT T2.results, T1.zip FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no WHERE T1.license_no = 1222441 | [
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4,028 | professional_basketball | bird:train.json:2903 | Which winning team in the 1947 playoff quarterfinals managed to score 3,513 defensive points that same year? | SELECT T2.tmID FROM series_post AS T1 INNER JOIN teams AS T2 ON T1.tmIDWinner = T2.tmID WHERE T1.year = 1947 AND T1.round = 'QF' AND T2.d_pts = 3513 | [
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4,029 | soccer_2016 | bird:train.json:1839 | Name the player who is born on July 7, 1981. | SELECT Player_name FROM Player WHERE DOB = '1981-07-07' | [
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4,030 | insurance_fnol | spider:train_spider.json:910 | Which customer uses the most policies? Give me the customer name. | SELECT t1.customer_name FROM customers AS t1 JOIN customers_policies AS t2 ON t1.customer_id = t2.customer_id GROUP BY t1.customer_name ORDER BY count(*) DESC LIMIT 1 | [
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4,031 | mondial_geo | bird:train.json:8267 | What is the average population growth rate of countries where more than 3 languages are used? | SELECT SUM(T3.Population_Growth) / COUNT(T3.Country) FROM country AS T1 INNER JOIN language AS T2 ON T1.Code = T2.Country INNER JOIN population AS T3 ON T3.Country = T2.Country WHERE T2.Country IN ( SELECT Country FROM language GROUP BY Country HAVING COUNT(Country) > 3 ) GROUP BY T3.Country | [
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4,032 | e_commerce | bird:test.json:113 | For all products sold more than 3 times, what are their ids and descriptions? | SELECT T1.product_id , T1.product_description FROM Products AS T1 JOIN Order_items AS T2 ON T1.product_id = T2.product_id GROUP BY T1.product_id HAVING count(*) > 3 | [
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4,034 | thrombosis_prediction | bird:dev.json:1236 | For all the female patient age 50 and above, who has abnormal red blood cell count. State if they were admitted to hospital. | SELECT DISTINCT T1.ID, T1.Admission FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T1.SEX = 'F' AND (T2.RBC <= 3.5 OR T2.RBC >= 6.0) AND STRFTIME('%Y', CURRENT_TIMESTAMP) - STRFTIME('%Y', T1.Birthday) >= 50 | [
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4,035 | retails | bird:train.json:6758 | Among all the customers in Brazil, how many of them have an account balance of less than 1000? | SELECT COUNT(T1.c_custkey) FROM customer AS T1 INNER JOIN nation AS T2 ON T1.c_nationkey = T2.n_nationkey WHERE T2.n_name = 'BRAZIL' AND T1.c_acctbal < 1000 | [
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4,036 | college_1 | spider:train_spider.json:3202 | How many credits does the department offer? | SELECT sum(crs_credit) , dept_code FROM course GROUP BY dept_code | [
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4,037 | flight_1 | spider:train_spider.json:430 | What are the names of all employees who are not certified to fly Boeing 737-800s? | SELECT name FROM Employee EXCEPT SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = "Boeing 737-800" | [
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4,038 | retail_world | bird:train.json:6577 | Identify the total number of orders placed by the customer 'Laughing Bacchus Wine Cellars' and it's average value. | SELECT COUNT(T2.OrderID) , SUM(T3.UnitPrice * T3.Quantity * (1 - T3.Discount)) / COUNT(T2.OrderID) FROM Customers AS T1 INNER JOIN Orders AS T2 ON T1.CustomerID = T2.CustomerID INNER JOIN `Order Details` AS T3 ON T2.OrderID = T3.OrderID WHERE T1.CompanyName = 'Laughing Bacchus Wine Cellars' | [
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4,039 | club_leader | bird:test.json:654 | Show the names of club leaders of clubs with overall ranking higher than 100. | SELECT T3.Name , T2.Club_Name FROM club_leader AS T1 JOIN club AS T2 ON T1.Club_ID = T2.Club_ID JOIN member AS T3 ON T1.Member_ID = T3.Member_ID WHERE T2.Overall_Ranking < 100 | [
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4,041 | codebase_comments | bird:train.json:620 | For the method which got the tokenized name as 't jadwal entity get single mpic', what is the path time for its solution? | SELECT DISTINCT T1.ProcessedTime FROM Solution AS T1 INNER JOIN Method AS T2 ON T1.Id = T2.SolutionId WHERE T2.NameTokenized = 't jadwal entity get single mpic' | [
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4,042 | car_retails | bird:train.json:1656 | When was the product with the highest unit price shipped? | SELECT t1.shippedDate FROM orders AS t1 INNER JOIN orderdetails AS t2 ON t1.orderNumber = t2.orderNumber ORDER BY t2.priceEach DESC LIMIT 1 | [
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4,043 | regional_sales | bird:train.json:2628 | Which product has the highest net profit in 2019? | SELECT T2.`Product Name` FROM `Sales Orders` AS T1 INNER JOIN Products AS T2 ON T2.ProductID = T1._ProductID WHERE T1.OrderDate LIKE '%/%/19' ORDER BY REPLACE(T1.`Unit Price`, ',', '') - REPLACE(T1.`Unit Cost`, ',', '') DESC LIMIT 1 | [
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4,044 | cre_Theme_park | spider:train_spider.json:5916 | Give me the detail and opening hour for each museum. | SELECT T1.Museum_Details , T2.Opening_Hours FROM MUSEUMS AS T1 JOIN TOURIST_ATTRACTIONS AS T2 ON T1.Museum_ID = T2.Tourist_Attraction_ID | [
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4,046 | retail_world | bird:train.json:6508 | Please calculate the number of orders from customers by country in 1996. | SELECT COUNT(T2.CustomerID) FROM Customers AS T1 INNER JOIN Orders AS T2 ON T1.CustomerID = T2.CustomerID WHERE STRFTIME('%Y', T2.OrderDate) = '1996' GROUP BY T1.Country | [
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4,047 | student_assessment | spider:train_spider.json:78 | What are the details of the student who registered for the most number of courses? | SELECT T1.student_details FROM students AS T1 JOIN student_course_registrations AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1 | [
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4,048 | financial | bird:dev.json:188 | Among the accounts who have loan validity more than 24 months, list out the accounts that have the lowest approved amount and have account opening date before 1997. | SELECT T1.account_id FROM loan AS T1 INNER JOIN account AS T2 ON T1.account_id = T2.account_id WHERE T1.duration > 24 AND STRFTIME('%Y', T2.date) < '1997' ORDER BY T1.amount ASC LIMIT 1 | [
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4,049 | performance_attendance | spider:train_spider.json:1314 | Show the most common location of performances. | SELECT LOCATION FROM performance GROUP BY LOCATION ORDER BY COUNT(*) DESC LIMIT 1 | [
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4,051 | sales_in_weather | bird:train.json:8149 | How many units of item no.5 were sold in store no.3 in total on days with a total precipitation of over 0.05? | SELECT SUM(CASE WHEN T3.preciptotal > 0.05 THEN units ELSE 0 END) AS sum FROM sales_in_weather AS T1 INNER JOIN relation AS T2 ON T1.store_nbr = T2.store_nbr INNER JOIN weather AS T3 ON T2.station_nbr = T3.station_nbr WHERE T2.store_nbr = 3 AND T1.item_nbr = 5 | [
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4,052 | restaurant | bird:train.json:1686 | In how many counties is there a street called Appian Way? | SELECT COUNT(DISTINCT T2.county) FROM location AS T1 INNER JOIN geographic AS T2 ON T1.city = T2.city WHERE T1.street_name = 'appian way' | [
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4,053 | public_review_platform | bird:train.json:3881 | List down the business ID with a star range from 2 to 3, located at Mesa. | SELECT business_id FROM Business WHERE city LIKE 'Mesa' AND stars BETWEEN 2 AND 3 | [
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4,054 | beer_factory | bird:train.json:5286 | List the full name and phone number of male customers from Fair Oaks who are subscribed to the email list. | SELECT First, Last, PhoneNumber FROM customers WHERE Gender = 'M' AND City = 'Fair Oaks' AND SubscribedToEmailList = 'TRUE' | [
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4,055 | food_inspection_2 | bird:train.json:6242 | What is the category of the inspection of the establishment named "J & J FOOD"? | SELECT DISTINCT T4.category FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no INNER JOIN violation AS T3 ON T2.inspection_id = T3.inspection_id INNER JOIN inspection_point AS T4 ON T3.point_id = T4.point_id WHERE T1.dba_name = 'J & J FOOD' | [
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4,056 | image_and_language | bird:train.json:7518 | What are the x and y coordinates of all the images with a prediction relationship class id of 98? | SELECT T2.X, T2.Y FROM IMG_REL AS T1 INNER JOIN IMG_OBJ AS T2 ON T1.IMG_ID = T2.IMG_ID WHERE T1.PRED_CLASS_ID = 98 | [
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4,057 | customer_complaints | spider:train_spider.json:5803 | Return the last name of the staff member who handled the complaint with the earliest date raised. | SELECT t1.last_name FROM staff AS t1 JOIN complaints AS t2 ON t1.staff_id = t2.staff_id ORDER BY t2.date_complaint_raised LIMIT 1 | [
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4,058 | gymnast | spider:train_spider.json:1763 | Return the hometown that is most common among gymnasts. | SELECT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID GROUP BY T2.Hometown ORDER BY COUNT(*) DESC LIMIT 1 | [
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4,059 | simpson_episodes | bird:train.json:4215 | List the award name and persons who won the award in 2009. | SELECT award, person FROM Award WHERE result = 'Winner' AND SUBSTR(year, 1, 4) = '2009'; | [
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4,060 | wrestler | spider:train_spider.json:1847 | What are the names of the wrestlers, ordered descending by days held? | SELECT Name FROM wrestler ORDER BY Days_held DESC | [
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4,062 | election | spider:train_spider.json:2765 | Which county do the delegates on "Appropriations" committee belong to? Give me the county names. | SELECT T1.County_name FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District WHERE T2.Committee = "Appropriations" | [
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4,063 | icfp_1 | spider:train_spider.json:2894 | Which paper is published in an institution in "USA" and have "Turon" as its second author? | SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid JOIN inst AS t4 ON t2.instid = t4.instid WHERE t4.country = "USA" AND t2.authorder = 2 AND t1.lname = "Turon" | [
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4,064 | music_4 | spider:train_spider.json:6186 | What are the categories of music festivals for which there have been more than 1 music festival? | SELECT Category FROM music_festival GROUP BY Category HAVING COUNT(*) > 1 | [
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4,066 | works_cycles | bird:train.json:7224 | List the first names of the people with more than 65 sick leave hours. | SELECT T2.FirstName FROM Employee AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE T1.SickLeaveHours > 65 | [
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4,067 | restaurant | bird:train.json:1723 | Which chicken restaurant has the highest review? | SELECT label FROM generalinfo WHERE food_type = 'chicken' ORDER BY review DESC LIMIT 1 | [
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4,068 | language_corpus | bird:train.json:5747 | How many times does the Catalan word "nombre" repeat itself? | SELECT T1.occurrences FROM langs_words AS T1 INNER JOIN words AS T2 ON T1.wid = T2.wid WHERE T2.word = 'nombre' | [
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4,069 | books | bird:train.json:6104 | Give the publisher's name of the books authored by Alan Lee. | SELECT T4.publisher_name FROM book AS T1 INNER JOIN book_author AS T2 ON T1.book_id = T2.book_id INNER JOIN author AS T3 ON T3.author_id = T2.author_id INNER JOIN publisher AS T4 ON T4.publisher_id = T1.publisher_id WHERE T3.author_name = 'Alan Lee' GROUP BY T4.publisher_name | [
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4,070 | sales_in_weather | bird:train.json:8187 | Which station sold the highest quantity of item number 5 overall? | SELECT T2.station_nbr FROM sales_in_weather AS T1 INNER JOIN relation AS T2 ON T1.store_nbr = T2.store_nbr WHERE T1.item_nbr = 5 GROUP BY T2.station_nbr ORDER BY SUM(T1.units) DESC LIMIT 1 | [
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4,071 | insurance_policies | spider:train_spider.json:3855 | What are the method, date and amount of each payment? Sort the list in ascending order of date. | SELECT Payment_Method_Code , Date_Payment_Made , Amount_Payment FROM Payments ORDER BY Date_Payment_Made ASC | [
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4,072 | superstore | bird:train.json:2407 | List the name of all products in the west superstore that customers chose for same-day shipment in the year 2013. | SELECT T2.`Product Name` FROM west_superstore AS T1 INNER JOIN product AS T2 ON T1.`Product ID` = T2.`Product ID` WHERE T1.`Ship Mode` = 'Same Day' AND T1.`Ship Date` LIKE '2013%' | [
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"value": "west_superstore"
},
{
"id": 0,
"type": "column",
"value": "Product Name"
},
{
"id": 3,
"type": "column",
"value": "Product ID"
},
{
"id": 4,
"type": "column",
"value": "Ship Mode"
},
{
"id": 6,
"type": "col... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8,
9
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
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6
]
},
{
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},
{
"entity_id":... | [
"O",
"O",
"O",
"O",
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"O",
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"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
4,074 | video_games | bird:train.json:3465 | List down the platform IDs of the games released in 2007. | SELECT DISTINCT T.platform_id FROM game_platform AS T WHERE T.release_year = 2007 | [
"List",
"down",
"the",
"platform",
"IDs",
"of",
"the",
"games",
"released",
"in",
"2007",
"."
] | [
{
"id": 0,
"type": "table",
"value": "game_platform"
},
{
"id": 2,
"type": "column",
"value": "release_year"
},
{
"id": 1,
"type": "column",
"value": "platform_id"
},
{
"id": 3,
"type": "value",
"value": "2007"
}
] | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id"... | [
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
4,075 | county_public_safety | spider:train_spider.json:2564 | List the names of counties that do not have any cities. | SELECT Name FROM county_public_safety WHERE County_ID NOT IN (SELECT County_ID FROM city) | [
"List",
"the",
"names",
"of",
"counties",
"that",
"do",
"not",
"have",
"any",
"cities",
"."
] | [
{
"id": 0,
"type": "table",
"value": "county_public_safety"
},
{
"id": 2,
"type": "column",
"value": "county_id"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "table",
"value": "city"
}
] | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
... | [
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
4,076 | book_1 | bird:test.json:587 | Show all book isbns which were ordered by both client Peter Doe and client James Smith. | SELECT T2.isbn FROM Orders AS T1 JOIN Books_Order AS T2 ON T1.idOrder = T2.idOrder JOIN Client AS T3 ON T1.idClient = T3.idClient WHERE T3.name = "Peter Doe" INTERSECT SELECT T2.isbn FROM Orders AS T1 JOIN Books_Order AS T2 ON T1.idOrder = T2.idOrder JOIN Client AS T3 ON T1.idClient = T3.idClient WHERE T3.nam... | [
"Show",
"all",
"book",
"isbns",
"which",
"were",
"ordered",
"by",
"both",
"client",
"Peter",
"Doe",
"and",
"client",
"James",
"Smith",
"."
] | [
{
"id": 4,
"type": "column",
"value": "James Smith"
},
{
"id": 6,
"type": "table",
"value": "books_order"
},
{
"id": 3,
"type": "column",
"value": "Peter Doe"
},
{
"id": 7,
"type": "column",
"value": "idclient"
},
{
"id": 8,
"type": "column",
... | [
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": [
10,
11
]
},
{
"entity_id": 4,
"token_idxs": [
15
... | [
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"B-COLUMN",
"B-COLUMN",
"O"
] |
4,077 | election_representative | spider:train_spider.json:1174 | How many elections are there? | SELECT count(*) FROM election | [
"How",
"many",
"elections",
"are",
"there",
"?"
] | [
{
"id": 0,
"type": "table",
"value": "election"
}
] | [
{
"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"
] |
4,078 | world_development_indicators | bird:train.json:2171 | What are the years when countries have indicator name of "Air transport, passengers carried"? List the table name of these countries. | SELECT DISTINCT T2.Year, T1.TableName FROM Country AS T1 INNER JOIN Indicators AS T2 ON T1.CountryCode = T2.CountryCode WHERE T2.IndicatorName = 'Air transport, passengers carried' | [
"What",
"are",
"the",
"years",
"when",
"countries",
"have",
"indicator",
"name",
"of",
"\"",
"Air",
"transport",
",",
"passengers",
"carried",
"\"",
"?",
"List",
"the",
"table",
"name",
"of",
"these",
"countries",
"."
] | [
{
"id": 5,
"type": "value",
"value": "Air transport, passengers carried"
},
{
"id": 4,
"type": "column",
"value": "indicatorname"
},
{
"id": 6,
"type": "column",
"value": "countrycode"
},
{
"id": 3,
"type": "table",
"value": "indicators"
},
{
"id":... | [
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
20,
21
]
},
{
"entity_id": 2,
"token_idxs": [
24
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
8
... | [
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
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"I-VALUE",
"I-VALUE",
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"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
4,079 | music_2 | spider:train_spider.json:5219 | What is the song with the most vocals? | SELECT title FROM vocals AS T1 JOIN songs AS T2 ON T1.songid = T2.songid GROUP BY T1.songid ORDER BY count(*) DESC LIMIT 1 | [
"What",
"is",
"the",
"song",
"with",
"the",
"most",
"vocals",
"?"
] | [
{
"id": 0,
"type": "column",
"value": "songid"
},
{
"id": 2,
"type": "table",
"value": "vocals"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "table",
"value": "songs"
}
] | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": ... | [
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
4,080 | world | bird:train.json:7831 | Among the languages used in Baltic Countries, provide the languages which are used by over 80%.
| SELECT T2.Language FROM Country AS T1 INNER JOIN CountryLanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Region = 'Baltic Countries' AND T2.Percentage > 80 | [
"Among",
"the",
"languages",
"used",
"in",
"Baltic",
"Countries",
",",
"provide",
"the",
"languages",
"which",
"are",
"used",
"by",
"over",
"80",
"%",
".",
"\n\n"
] | [
{
"id": 6,
"type": "value",
"value": "Baltic Countries"
},
{
"id": 2,
"type": "table",
"value": "countrylanguage"
},
{
"id": 4,
"type": "column",
"value": "countrycode"
},
{
"id": 7,
"type": "column",
"value": "percentage"
},
{
"id": 0,
"type":... | [
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
... | [
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
4,081 | authors | bird:train.json:3604 | What is the average number of papers published in the World Computer Congress each year? | SELECT CAST(SUM(CASE WHEN T2.FullName = 'International Congress Series' THEN 1 ELSE 0 END) AS REAL) / COUNT(T1.Id) AS Div1, T1.Year FROM Paper AS T1 INNER JOIN Journal AS T2 ON T1.JournalId = T2.Id GROUP BY T1.YEAR HAVING Div1 != 0 | [
"What",
"is",
"the",
"average",
"number",
"of",
"papers",
"published",
"in",
"the",
"World",
"Computer",
"Congress",
"each",
"year",
"?"
] | [
{
"id": 9,
"type": "value",
"value": "International Congress Series"
},
{
"id": 5,
"type": "column",
"value": "journalid"
},
{
"id": 8,
"type": "column",
"value": "fullname"
},
{
"id": 2,
"type": "table",
"value": "journal"
},
{
"id": 1,
"type"... | [
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"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-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
4,083 | cre_Students_Information_Systems | bird:test.json:463 | Which students only got the most common result for his or her all behaviour monitoring details? List the students' biographical information. | SELECT T1.bio_data FROM Students AS T1 JOIN Behaviour_Monitoring AS T2 ON T1.student_id = T2.student_id WHERE T2.behaviour_monitoring_details IN ( SELECT behaviour_monitoring_details FROM Behaviour_Monitoring GROUP BY behaviour_monitoring_details ORDER BY count(*) DESC LIMIT 1 ) EXCEPT SELECT T1.bio_data FROM Student... | [
"Which",
"students",
"only",
"got",
"the",
"most",
"common",
"result",
"for",
"his",
"or",
"her",
"all",
"behaviour",
"monitoring",
"details",
"?",
"List",
"the",
"students",
"'",
"biographical",
"information",
"."
] | [
{
"id": 3,
"type": "column",
"value": "behaviour_monitoring_details"
},
{
"id": 2,
"type": "table",
"value": "behaviour_monitoring"
},
{
"id": 4,
"type": "column",
"value": "student_id"
},
{
"id": 0,
"type": "column",
"value": "bio_data"
},
{
"id":... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
19
]
},
{
"entity_id": 2,
"token_idxs": [
13,
14
]
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": [
1
]
},
{... | [
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
4,084 | movies_4 | bird:train.json:443 | What is the name of the production company that made the most movies? | SELECT T1.company_name FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id GROUP BY T1.company_id ORDER BY COUNT(T2.movie_id) DESC LIMIT 1 | [
"What",
"is",
"the",
"name",
"of",
"the",
"production",
"company",
"that",
"made",
"the",
"most",
"movies",
"?"
] | [
{
"id": 2,
"type": "table",
"value": "production_company"
},
{
"id": 3,
"type": "table",
"value": "movie_company"
},
{
"id": 1,
"type": "column",
"value": "company_name"
},
{
"id": 0,
"type": "column",
"value": "company_id"
},
{
"id": 4,
"type"... | [
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
... | [
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
4,085 | cars | bird:train.json:3076 | What is the maximum sweep volume of a car that costs less than $30000? | SELECT MAX(T1.displacement / T1.cylinders) FROM data AS T1 INNER JOIN price AS T2 ON T1.ID = T2.ID WHERE T2.price < 30000 | [
"What",
"is",
"the",
"maximum",
"sweep",
"volume",
"of",
"a",
"car",
"that",
"costs",
"less",
"than",
"$",
"30000",
"?"
] | [
{
"id": 5,
"type": "column",
"value": "displacement"
},
{
"id": 6,
"type": "column",
"value": "cylinders"
},
{
"id": 1,
"type": "table",
"value": "price"
},
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 3,
"type": "value",
"value... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
... | [
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
4,086 | allergy_1 | spider:train_spider.json:446 | What are the allergies and their types? | SELECT allergy , allergytype FROM Allergy_type | [
"What",
"are",
"the",
"allergies",
"and",
"their",
"types",
"?"
] | [
{
"id": 0,
"type": "table",
"value": "allergy_type"
},
{
"id": 2,
"type": "column",
"value": "allergytype"
},
{
"id": 1,
"type": "column",
"value": "allergy"
}
] | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
... | [
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
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