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425 | planet_1 | bird:test.json:1881 | Who sent most number of packages? List client name and number of packages sent by that client. | SELECT T2.Name , count(*) FROM PACKAGE AS T1 JOIN Client AS T2 ON T1.Sender = T2.AccountNumber GROUP BY T1.Sender ORDER BY count(*) DESC LIMIT 1; | [
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426 | solvency_ii | spider:train_spider.json:4588 | What is the name of the product with the highest price? | SELECT Product_Name FROM Products ORDER BY Product_Price DESC LIMIT 1 | [
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427 | thrombosis_prediction | bird:dev.json:1157 | For patients with severe degree of thrombosis, list their ID, sex and disease the patient is diagnosed with. | SELECT DISTINCT T1.ID, T1.SEX, T1.Diagnosis FROM Patient AS T1 INNER JOIN Examination AS T2 ON T1.ID = T2.ID WHERE T2.Thrombosis = 2 | [
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428 | cre_Doc_and_collections | bird:test.json:673 | What is the owner of document with the Description 'Braeden Collection'? | SELECT OWNER FROM Document_Objects WHERE Description = 'Braeden Collection' | [
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429 | government_shift | bird:test.json:377 | Find the name of all the services which either have been used by customer "Hardy Kutch" or have been rated as "good" in one of the customer interactions. | SELECT DISTINCT t3.service_details FROM customers AS t1 JOIN customers_and_services AS t2 ON t1.customer_id = t2.customer_id JOIN services AS t3 ON t2.service_id = t3.service_id JOIN customer_interactions AS t4 ON t3.service_id = t4.service_id WHERE t1.customer_details = "Hardy Kutch" OR t4.services_and_channels_details = "good" | [
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430 | codebase_comments | bird:train.json:638 | List all the solutions ids of the repository with "636430969128176000" processed time | SELECT T2.Id FROM Repo AS T1 INNER JOIN Solution AS T2 ON T1.Id = T2.RepoId WHERE T1.ProcessedTime = 636430969128176000 | [
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431 | sing_contest | bird:test.json:759 | Which song names have the substring "Is"? | SELECT name FROM songs WHERE name LIKE "%Is%" | [
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432 | public_review_platform | bird:train.json:4132 | Among the active businesses located at Goodyear, AZ, list the category and atrributes of business with a high review count. | SELECT T3.category_name, T5.attribute_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 INNER JOIN Business_Attributes AS T4 ON T1.business_id = T4.business_id INNER JOIN Attributes AS T5 ON T4.attribute_id = T5.attribute_id WHERE T1.review_count = 'High' AND T1.city = 'Goodyear' AND T1.state = 'AZ' AND T1.active = 'true' | [
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433 | codebase_comments | bird:train.json:566 | How many English language codes whose comments for the method are in the XML format? | SELECT COUNT(Lang) FROM Method WHERE Lang = 'en' AND CommentIsXml = 1 | [
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435 | manufactory_1 | spider:train_spider.json:5277 | What are the names and headquarters of all manufacturers, ordered by revenue descending? | SELECT name , headquarter FROM manufacturers ORDER BY revenue DESC | [
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436 | manufactory_1 | spider:train_spider.json:5327 | What are the names of products with price at most 200? | SELECT name FROM products WHERE price <= 200 | [
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437 | law_episode | bird:train.json:1305 | How many votes did the episode titled Juvenile get? | SELECT SUM(T2.votes) FROM Episode AS T1 INNER JOIN Vote AS T2 ON T1.episode_id = T2.episode_id WHERE T1.title = 'Juvenile' | [
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438 | works_cycles | bird:train.json:7222 | How many customers are there in Canada? | SELECT COUNT(T2.CustomerID) FROM SalesTerritory AS T1 INNER JOIN Customer AS T2 ON T1.TerritoryID = T2.TerritoryID WHERE T1.Name = 'Canada' | [
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439 | simpson_episodes | bird:train.json:4303 | Which country has the tallest person in the crew? | SELECT birth_country FROM Person ORDER BY height_meters DESC LIMIT 1; | [
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440 | food_inspection | bird:train.json:8850 | List the violation type ID of business with business ID from 30 to 50 and located at 747 IRVING St, San Francisco. | SELECT DISTINCT T1.violation_type_id FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T2.business_id BETWEEN 30 AND 50 AND T2.address = '747 IRVING St' AND T2.city = 'San Francisco' | [
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442 | allergy_1 | spider:train_spider.json:474 | How many students are 18 years old? | SELECT count(*) FROM Student WHERE age = 18 | [
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443 | retail_world | bird:train.json:6660 | Give the phone number of the customer who placed the order id 10264. | SELECT T1.Phone FROM Customers AS T1 INNER JOIN Orders AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.OrderID = 10264 | [
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445 | movie_3 | bird:train.json:9328 | Please provide the address of the customer whose first name is SUSAN with the postal code 77948. | SELECT T1.address FROM address AS T1 INNER JOIN customer AS T2 ON T1.address_id = T2.address_id WHERE T2.first_name = 'SUSAN' AND T1.postal_code = 77948 | [
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446 | financial | bird:dev.json:132 | What is the average loan amount by male borrowers? | SELECT AVG(T4.amount) FROM client AS T1 INNER JOIN disp AS T2 ON T1.client_id = T2.client_id INNER JOIN account AS T3 ON T2.account_id = T3.account_id INNER JOIN loan AS T4 ON T3.account_id = T4.account_id WHERE T1.gender = 'M' | [
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447 | movie_1 | spider:train_spider.json:2523 | What are the ids of all reviewers who have not given 4 stars at least once? | SELECT rID FROM Rating WHERE stars != 4 | [
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448 | network_2 | spider:train_spider.json:4466 | Who has friends that are older than the average age? Print their friends and their ages as well | SELECT DISTINCT T2.name , T2.friend , T1.age FROM Person AS T1 JOIN PersonFriend AS T2 ON T1.name = T2.friend WHERE T1.age > (SELECT avg(age) FROM person) | [
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449 | soccer_2016 | bird:train.json:1795 | Please list the names of the players who use the right hand as their batting hand and are from Australia. | SELECT T2.Player_Name FROM Country AS T1 INNER JOIN Player AS T2 ON T2.Country_Name = T1.Country_id INNER JOIN Batting_Style AS T3 ON T2.Batting_hand = T3.Batting_Id WHERE T1.Country_Name = 'Australia' AND T3.Batting_Hand = 'Right-hand bat' | [
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450 | sales_in_weather | bird:train.json:8204 | How many units of item 7 have been sold by store 7 when the snow is less than 5 inches? | SELECT SUM(units) FROM weather AS T1 INNER JOIN relation AS T2 ON T1.station_nbr = T2.station_nbr INNER JOIN sales_in_weather AS T3 ON T2.store_nbr = T3.store_nbr WHERE T2.store_nbr = 7 AND T3.item_nbr = 7 AND T1.snowfall < 5 | [
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451 | world | bird:train.json:7916 | Among the cities with a population between 140000 and 150000, list the country that has life expectancy greater than 80% life expectancy of all countries. | SELECT T2.Name FROM City AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.Code WHERE T1.Population BETWEEN 140000 AND 150000 GROUP BY T2.Name, LifeExpectancy HAVING LifeExpectancy < ( SELECT AVG(LifeExpectancy) FROM Country ) * 0.8 | [
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453 | regional_sales | bird:train.json:2629 | What is the average unit price of a Cookware product? | SELECT AVG(REPLACE(T1.`Unit Price`, ',', '')) FROM `Sales Orders` AS T1 INNER JOIN Products AS T2 ON T2.ProductID = T1._ProductID WHERE T2.`Product Name` = 'Cookware' | [
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454 | legislator | bird:train.json:4755 | Among all the current legislators whose religion is Roman Catholic, what is the percentage of the ones without an instagram account? | SELECT CAST(SUM(CASE WHEN T1.instagram IS NULL THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM `social-media` AS T1 INNER JOIN current AS T2 ON T1.bioguide = T2.bioguide_id WHERE T2.religion_bio = 'Roman Catholic' | [
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455 | codebase_community | bird:dev.json:602 | List out all post ID with score more than 60 and list out all the user ID that created these post. | SELECT PostId, UserId FROM postHistory WHERE PostId IN ( SELECT Id FROM posts WHERE Score > 60 ) | [
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456 | driving_school | spider:train_spider.json:6665 | What is the status code, phone number, and email address of the customer whose last name is Kohler or whose first name is Marina? | SELECT customer_status_code , cell_mobile_phone_number , email_address FROM Customers WHERE first_name = "Marina" OR last_name = "Kohler" | [
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457 | activity_1 | spider:train_spider.json:6771 | Show the ids of the faculty who don't participate in any activity. | SELECT FacID FROM Faculty EXCEPT SELECT FacID FROM Faculty_participates_in | [
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458 | cre_Doc_Workflow | bird:test.json:2019 | Show the names and other details for all authors. | SELECT author_name , other_details FROM Authors | [
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459 | advertising_agencies | bird:test.json:2062 | How many clients are there? | SELECT count(*) FROM Clients | [
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"id": 0,
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460 | books | bird:train.json:5921 | Please list the titles of all the books in British English. | SELECT T1.title FROM book AS T1 INNER JOIN book_language AS T2 ON T1.language_id = T2.language_id WHERE T2.language_name = 'British English' | [
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461 | software_company | bird:train.json:8582 | Find the response status to customer whose geographic ID of 134. | SELECT T2.RESPONSE FROM Customers AS T1 INNER JOIN mailings3 AS T2 ON T1.ID = T2.REFID WHERE T1.GEOID = 134 | [
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462 | student_club | bird:dev.json:1368 | What does the person with the phone number "809-555-3360" major in? | SELECT T2.major_name FROM member AS T1 INNER JOIN major AS T2 ON T1.link_to_major = T2.major_id WHERE T1.phone = '809-555-3360' | [
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463 | wine_1 | spider:train_spider.json:6525 | List the names and scores of all wines. | SELECT Name , Score FROM WINE | [
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464 | customers_and_orders | bird:test.json:292 | What were the ids, dates, and status codes for orders made by Jeromy? | SELECT order_id , order_date , order_status_code FROM Customer_orders AS T1 JOIN Customers AS T2 ON T1.customer_id = T2.customer_id WHERE T2.customer_name = "Jeromy" | [
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465 | e_learning | spider:train_spider.json:3833 | On what dates did the student whose personal name is "Karson" enroll in and complete the courses? | SELECT T1.date_of_enrolment , T1.date_of_completion FROM Student_Course_Enrolment AS T1 JOIN Students AS T2 ON T1.student_id = T2.student_id WHERE T2.personal_name = "Karson" | [
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466 | app_store | bird:train.json:2543 | List all the comments on the lowest rated Mature 17+ app. | SELECT T2.Translated_Review FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1."Content Rating" = 'Mature 17+' ORDER BY T1.Rating LIMIT 1 | [
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467 | public_review_platform | bird:train.json:3884 | Among the businesses in Chandler, list the attribute of the business with a low review count. | SELECT DISTINCT T3.attribute_id, T3.attribute_name FROM Business AS T1 INNER JOIN Business_Attributes AS T2 ON T1.business_id = T2.attribute_id INNER JOIN Attributes AS T3 ON T2.attribute_id = T3.attribute_id WHERE T1.review_count = 'Low' AND T1.city = 'Chandler' | [
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468 | food_inspection_2 | bird:train.json:6153 | What are the comments of the inspector during the inspection of Taqueria La Fiesta on 1/25/2010? | SELECT T3.inspector_comment 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 WHERE T2.inspection_date = '2010-01-25' AND T1.dba_name = 'TAQUERIA LA FIESTA' | [
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469 | movielens | bird:train.json:2275 | What is the difference of female and male audiences in number who viewed horror movies? | SELECT SUM(IIF(T2.u_gender = 'F', 1, 0)) - SUM(IIF(T2.u_gender = 'M', 1, 0)) FROM u2base AS T1 INNER JOIN users AS T2 ON T1.userid = T2.userid INNER JOIN movies2directors AS T3 ON T3.movieid = T1.movieid WHERE T3.genre = 'horror' | [
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470 | mondial_geo | bird:train.json:8499 | Which nation, with a population ranging from 60,000,000 to 99,000,000, has the greatest gross domestic product? | SELECT T1.Name, T2.GDP FROM country AS T1 INNER JOIN economy AS T2 ON T1.Code = T2.Country WHERE T1.Population BETWEEN 60000000 AND 90000000 ORDER BY T2.GDP DESC LIMIT 1 | [
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471 | hr_1 | spider:train_spider.json:3500 | What are the full names and hire dates for employees in the same department as someone with the first name Clara? | SELECT first_name , last_name , hire_date FROM employees WHERE department_id = (SELECT department_id FROM employees WHERE first_name = "Clara") | [
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472 | movies_4 | bird:train.json:420 | Among the movie in which Dariusz Wolski works as the director of photography, what is the percentage of those movie whose vote average is over 5.0? | SELECT CAST(COUNT(CASE WHEN T1.vote_average > 5 THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T1.vote_average) FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T3.person_name = 'Dariusz Wolski' AND T2.job = 'Director of Photography' | [
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473 | retail_complains | bird:train.json:284 | Calculate the average number of complaints received from New Bedford each year which are closed with explanation. | SELECT STRFTIME('%Y', T3.`Date received`) , CAST(SUM(CASE WHEN T3.`Company response to consumer` = 'Closed with explanation' THEN 1 ELSE 0 END) AS REAL) / COUNT(T3.`Complaint ID`) AS average FROM callcenterlogs AS T1 INNER JOIN client AS T2 ON T1.`rand client` = T2.client_id INNER JOIN events AS T3 ON T1.`Complaint ID` = T3.`Complaint ID` WHERE T2.city = 'New Bedford' GROUP BY strftime('%Y', T3.`Date received`) | [
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474 | computer_student | bird:train.json:998 | Please list the IDs of the top 3 professors that teaches the most courses. | SELECT T1.p_id FROM taughtBy AS T1 INNER JOIN person AS T2 ON T1.p_id = T2.p_id WHERE T2.professor = 1 GROUP BY T1.p_id ORDER BY COUNT(*) DESC LIMIT 3 | [
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476 | donor | bird:train.json:3181 | How many schools in urban area requested for books resources? | SELECT COUNT(T2.schoolid) FROM resources AS T1 INNER JOIN projects AS T2 ON T1.projectid = T2.projectid WHERE T2.resource_type = 'Books' AND T2.school_metro = 'urban' | [
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"id": 0,
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477 | insurance_and_eClaims | spider:train_spider.json:1525 | How many claim processing stages are there in total? | SELECT count(*) FROM claims_processing_stages | [
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478 | retails | bird:train.json:6729 | List any five parts name in Medium Plated Brass. | SELECT p_name FROM part WHERE p_type = 'MEDIUM PLATED BRASS' LIMIT 5 | [
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"type": "column",
"value": "p_type"
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479 | hockey | bird:train.json:7765 | Please list the first names of the coaches who have taught the Montreal Canadiens. | SELECT DISTINCT T3.firstName FROM Coaches AS T1 INNER JOIN Teams AS T2 ON T1.year = T2.year AND T1.tmID = T2.tmID INNER JOIN Master AS T3 ON T1.coachID = T3.coachID WHERE T2.name = 'Montreal Canadiens' | [
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480 | public_review_platform | bird:train.json:3834 | How many businesses are there in Scottsdale city under the category of "Beauty & Spas"? | SELECT COUNT(T2.business_id) FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business AS T3 ON T2.business_id = T3.business_id WHERE T3.city LIKE 'Scottsdale' AND T1.category_name LIKE 'Beauty & Spas' | [
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] |
481 | vehicle_rent | bird:test.json:421 | Show all information for all discounts. | SELECT * FROM discount | [
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482 | donor | bird:train.json:3245 | For the all donations to the project 'Bringing Drama to Life', what is the percentage of the donation is paid by credit card? | SELECT CAST(SUM(CASE WHEN T2.payment_method LIKE 'creditcard' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(donationid) FROM essays AS T1 INNER JOIN donations AS T2 ON T1.projectid = T2.projectid WHERE T1.title LIKE 'Bringing Drama to Life' | [
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483 | simpson_episodes | bird:train.json:4281 | What is the number of votes for 10-star for the episode that has the keyword "reference to the fantastic four"? | SELECT T2.votes FROM Keyword AS T1 INNER JOIN Vote AS T2 ON T1.episode_id = T2.episode_id WHERE T2.stars = 10 AND T1.keyword = 'reference to the fantastic four'; | [
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484 | department_store | spider:train_spider.json:4792 | What are the ids and names of customers with addressed that contain WY and who do not use a credit card for payment? | SELECT customer_id , customer_name FROM customers WHERE customer_address LIKE "%WY%" AND payment_method_code != "Credit Card" | [
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485 | cre_Students_Information_Systems | bird:test.json:452 | Return the distinct descriptions of all the detentions that have happened. | SELECT distinct(T1.detention_type_description) FROM Ref_Detention_Type AS T1 JOIN Detention AS T2 ON T1.detention_type_code = T2.detention_type_code | [
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486 | flight_1 | spider:train_spider.json:357 | Show the name of aircrafts with top three lowest distances. | SELECT name FROM Aircraft ORDER BY distance LIMIT 3 | [
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"id": 0,
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487 | film_rank | spider:train_spider.json:4129 | What are the countries for each market ordered by decreasing number of cities? | SELECT Country FROM market ORDER BY Number_cities DESC | [
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489 | college_2 | spider:train_spider.json:1404 | Find the year which offers the largest number of courses. | SELECT YEAR FROM SECTION GROUP BY YEAR ORDER BY count(*) DESC LIMIT 1 | [
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490 | movie_3 | bird:train.json:9149 | Tell the special features of the film Uprising Uptown. | SELECT special_features FROM film WHERE title = 'UPRISING UPTOWN' | [
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491 | movie_3 | bird:train.json:9109 | How many films with the rental rate of $2.99 have the special feature of "Deleted Scenes"? | SELECT COUNT(film_id) FROM film WHERE rental_rate = 2.99 AND special_features = 'Deleted Scenes' | [
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492 | program_share | spider:train_spider.json:3756 | List all program origins in the alphabetical order. | SELECT origin FROM program ORDER BY origin | [
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493 | movie_platform | bird:train.json:160 | What are the top 5 most popular movies of the 21st century? Indicate how many users gave it a rating score of 5. | SELECT DISTINCT T2.movie_id, SUM(T1.rating_score = 5) FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id ORDER BY T2.movie_popularity DESC LIMIT 5 | [
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494 | book_1 | bird:test.json:589 | Find the title of books which are ordered by client Peter Doe but not client James Smith. | SELECT T4.title FROM Orders AS T1 JOIN Books_Order AS T2 ON T1.idOrder = T2.idOrder JOIN Client AS T3 ON T1.idClient = T3.idClient JOIN book AS T4 ON T2.ISBN = T4.isbn WHERE T3.name = "Peter Doe" EXCEPT SELECT T4.title FROM Orders AS T1 JOIN Books_Order AS T2 ON T1.idOrder = T2.idOrder JOIN Client AS T3 ON T1.idClient = T3.idClient JOIN book AS T4 ON T2.ISBN = T4.isbn WHERE T3.name = "James Smith" | [
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495 | sales_in_weather | bird:train.json:8180 | Between 1/1/2012 to 12/31/2014, which date recorded the hottest temperature in weather station 1? | SELECT `date` FROM weather WHERE station_nbr = 1 AND CAST(SUBSTR(`date`, 1, 4) AS int) BETWEEN 2012 AND 2014 ORDER BY tmax DESC LIMIT 1 | [
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496 | codebase_comments | bird:train.json:682 | What is the github address of the solution path "joeyrobert_bloomfilter\DataTypes.BloomFilter.sln"? | SELECT T1.Url FROM Repo AS T1 INNER JOIN Solution AS T2 ON T1.Id = T2.RepoId WHERE T2.Path = 'joeyrobert_bloomfilterDataTypes.BloomFilter.sln' | [
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497 | food_inspection | bird:train.json:8815 | Among the establishments with a postal code of 94102, how many establishments have a score of 90 or more in 2015? | SELECT COUNT(DISTINCT T2.business_id) FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id INNER JOIN inspections AS T3 ON T2.business_id = T3.business_id WHERE STRFTIME('%Y', T1.`date`) = '2015' AND T2.postal_code = '94102' AND T3.score > 90 | [
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498 | card_games | bird:dev.json:507 | For all the set of cards that has Brazil Portuguese translation, what is the percentage of them are only available online? | SELECT CAST(SUM(CASE WHEN isOnlineOnly = 1 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(id) FROM sets WHERE code IN ( SELECT setCode FROM set_translations WHERE language = 'Portuguese (Brazil)' ) | [
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499 | movie_platform | bird:train.json:150 | List all movies rated by user 39115684. State the title, rating date and rating score. | SELECT T2.movie_title, T1.rating_timestamp_utc, T1.rating_score FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T1.user_id = 39115684 | [
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500 | headphone_store | bird:test.json:959 | How many headphones are stored in the Woodman store? | SELECT sum(t2.quantity) FROM store AS t1 JOIN stock AS t2 ON t1.store_id = t2.store_id WHERE t1.name = 'Woodman' | [
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"id": 4,
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501 | products_gen_characteristics | spider:train_spider.json:5526 | Find the names of all the product characteristics. | SELECT DISTINCT characteristic_name FROM CHARACTERISTICS | [
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"id": 1,
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502 | video_games | bird:train.json:3411 | What percentage of games are sports? | SELECT CAST(COUNT(CASE WHEN T1.genre_name = 'Sports' THEN T2.id ELSE NULL END) AS REAL) * 100 / COUNT(T2.id) FROM genre AS T1 INNER JOIN game AS T2 ON T1.id = T2.genre_id | [
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"id": 0,
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503 | music_platform_2 | bird:train.json:7975 | What is the content of the earliest review for the "Stuff You Should Know" podcast? | SELECT T2.content FROM podcasts AS T1 INNER JOIN reviews AS T2 ON T2.podcast_id = T1.podcast_id WHERE T1.title = 'Stuff You Should Know' ORDER BY T2.created_at ASC LIMIT 1 | [
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504 | mondial_geo | bird:train.json:8474 | List all countries with 'Category III' membership in 'IFAD' organization. Please also provide the capital of the country. | SELECT Name, Capital FROM country WHERE Code IN ( SELECT Country FROM isMember WHERE type = 'Category III' AND Organization = 'IFAD' ) | [
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505 | school_player | spider:train_spider.json:4897 | What are the nicknames of schools whose division is not 1? | SELECT Nickname FROM school_details WHERE Division != "Division 1" | [
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506 | movie_3 | bird:train.json:9415 | Among all the customers of store no.1, how many of them are active? | SELECT COUNT(customer_id) FROM customer WHERE active = 1 AND store_id = 1 | [
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507 | movie_3 | bird:train.json:9254 | Give the total amount of rent for the movie Clockwork Paradice. | SELECT SUM(T1.amount) FROM payment AS T1 INNER JOIN rental AS T2 ON T1.rental_id = T2.rental_id INNER JOIN inventory AS T3 ON T2.inventory_id = T3.inventory_id INNER JOIN film AS T4 ON T3.film_id = T4.film_id WHERE T4.title = 'CLOCKWORK PARADICE' | [
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508 | formula_1 | spider:train_spider.json:2190 | For each constructor id, how many races are there? | SELECT count(*) , constructorid FROM constructorStandings GROUP BY constructorid | [
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509 | shipping | bird:train.json:5587 | What is the maximum weight being transported to New York during a single shipment? | SELECT MAX(T1.weight) FROM shipment AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.city_id WHERE T2.city_name = 'New York' | [
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510 | coinmarketcap | bird:train.json:6286 | What is the name of the coin that creates the most total value in the past 24 hours? | SELECT T1.name FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T2.volume_24h = ( SELECT MAX(volume_24h) FROM historical ) | [
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511 | student_loan | bird:train.json:4548 | Among students with 1 month of absenses, how many of them are enlisted in the air force department? | SELECT COUNT(T1.name) FROM longest_absense_from_school AS T1 INNER JOIN enlist AS T2 ON T1.name = T2.name WHERE T1.month = 1 AND T2.organ = 'air_force' | [
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512 | baseball_1 | spider:train_spider.json:3696 | Compute the total salary that the player with first name Len and last name Barker received between 1985 to 1990. | SELECT sum(T1.salary) FROM salary AS T1 JOIN player AS T2 ON T1.player_id = T2.player_id WHERE T2.name_first = 'Len' AND T2.name_last = 'Barker' AND T1.year BETWEEN 1985 AND 1990; | [
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513 | simpson_episodes | bird:train.json:4315 | What is the average heights of crew members from Animation Department? | SELECT AVG(T1.height_meters) FROM Person AS T1 INNER JOIN Credit AS T2 ON T1.name = T2.person WHERE T2.category = 'Animation Department'; | [
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515 | regional_sales | bird:train.json:2661 | What is the difference in order number from "WARE-MKL1006" and "WARE-NBV1002"? | SELECT SUM(IIF(WarehouseCode = 'WARE-MKL1006', 1, 0)) - SUM(IIF(WarehouseCode = 'WARE-NBV1002', 1, 0)) AS difference FROM `Sales Orders` | [
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516 | driving_school | spider:train_spider.json:6684 | Which country does customer with first name as Carole and last name as Bernhard lived in? | SELECT T2.country FROM Customers AS T1 JOIN Addresses AS T2 ON T1.customer_address_id = T2.address_id WHERE T1.first_name = "Carole" AND T1.last_name = "Bernhard" | [
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517 | works_cycles | bird:train.json:7093 | What is the job title of the newest employee in department 12? | SELECT T1.JobTitle FROM Employee AS T1 INNER JOIN EmployeeDepartmentHistory AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE T2.DepartmentID = 12 ORDER BY T2.StartDate DESC LIMIT 1 | [
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518 | loan_1 | spider:train_spider.json:3046 | Find the branch name of the bank that has the most number of customers. | SELECT bname FROM bank ORDER BY no_of_customers DESC LIMIT 1 | [
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519 | public_review_platform | bird:train.json:3788 | User No."63469" has got "1" like for a tip to the Yelp business, which city is that business located in? | SELECT T1.city FROM Business AS T1 INNER JOIN Tips AS T2 ON T1.business_id = T2.business_id WHERE T2.likes = 1 AND T2.user_id = 63469 | [
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"value... | [
{
"entity_id": 0,
"token_idxs": [
20
]
},
{
"entity_id": 1,
"token_idxs": [
17
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"ent... | [
"B-COLUMN",
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"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
521 | law_episode | bird:train.json:1276 | How many people, who were born in Canada, won an award in 1999? | SELECT COUNT(T1.person_id) FROM Person AS T1 INNER JOIN Award AS T2 ON T1.person_id = T2.person_id WHERE T2.year = 1999 AND T1.birth_country = 'Canada' | [
"How",
"many",
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",",
"who",
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"Canada",
",",
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"1999",
"?"
] | [
{
"id": 5,
"type": "column",
"value": "birth_country"
},
{
"id": 2,
"type": "column",
"value": "person_id"
},
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 6,
"type": "value",
"value": "Canada"
},
{
"id": 1,
"type": "table",
"val... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs"... | [
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
522 | image_and_language | bird:train.json:7575 | State the coordinate of X and Y for the object with the attribute of 'sparse' in image 1. | SELECT T3.OBJ_SAMPLE_ID, T3.X, T3.Y FROM ATT_CLASSES AS T1 INNER JOIN IMG_OBJ_ATT AS T2 ON T1.ATT_CLASS_ID = T2.ATT_CLASS_ID INNER JOIN IMG_OBJ AS T3 ON T2.IMG_ID = T3.IMG_ID WHERE T3.IMG_ID = 1 AND T1.ATT_CLASS = 'sparse' | [
"State",
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"coordinate",
"of",
"X",
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"Y",
"for",
"the",
"object",
"with",
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"attribute",
"of",
"'",
"sparse",
"'",
"in",
"image",
"1",
"."
] | [
{
"id": 0,
"type": "column",
"value": "obj_sample_id"
},
{
"id": 10,
"type": "column",
"value": "att_class_id"
},
{
"id": 4,
"type": "table",
"value": "att_classes"
},
{
"id": 5,
"type": "table",
"value": "img_obj_att"
},
{
"id": 8,
"type": "co... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": ... | [
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
523 | university | bird:train.json:8079 | Please list the names of the universities with a score in teaching of over 90 in 2011. | SELECT T3.university_name FROM ranking_criteria AS T1 INNER JOIN university_ranking_year AS T2 ON T1.id = T2.ranking_criteria_id INNER JOIN university AS T3 ON T3.id = T2.university_id WHERE T1.criteria_name = 'Teaching' AND T2.year = 2011 AND T2.score > 90 | [
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"the",
"names",
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"the",
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"with",
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"score",
"in",
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"of",
"over",
"90",
"in",
"2011",
"."
] | [
{
"id": 3,
"type": "table",
"value": "university_ranking_year"
},
{
"id": 12,
"type": "column",
"value": "ranking_criteria_id"
},
{
"id": 2,
"type": "table",
"value": "ranking_criteria"
},
{
"id": 0,
"type": "column",
"value": "university_name"
},
{
... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"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",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
524 | works_cycles | bird:train.json:7330 | Names the Sales Representative with the highest year to date sales. | SELECT T2.FirstName, T2.MiddleName, T2.LastName FROM SalesPerson AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID ORDER BY T1.SalesYTD DESC LIMIT 1 | [
"Names",
"the",
"Sales",
"Representative",
"with",
"the",
"highest",
"year",
"to",
"date",
"sales",
"."
] | [
{
"id": 6,
"type": "column",
"value": "businessentityid"
},
{
"id": 3,
"type": "table",
"value": "salesperson"
},
{
"id": 1,
"type": "column",
"value": "middlename"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 2,
"type": "col... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
0
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10
... | [
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
526 | movie_platform | bird:train.json:116 | Who was the earliest user created a list but didn't get any followers? Give the user ID. | SELECT user_id FROM lists_users WHERE user_subscriber = 0 ORDER BY list_creation_date_utc LIMIT 1 | [
"Who",
"was",
"the",
"earliest",
"user",
"created",
"a",
"list",
"but",
"did",
"n't",
"get",
"any",
"followers",
"?",
"Give",
"the",
"user",
"ID",
"."
] | [
{
"id": 4,
"type": "column",
"value": "list_creation_date_utc"
},
{
"id": 2,
"type": "column",
"value": "user_subscriber"
},
{
"id": 0,
"type": "table",
"value": "lists_users"
},
{
"id": 1,
"type": "column",
"value": "user_id"
},
{
"id": 3,
"ty... | [
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
17,
18
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5... | [
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
527 | music_4 | spider:train_spider.json:6152 | Give the distinct famous release dates for all artists. | SELECT distinct(Famous_Release_date) FROM artist | [
"Give",
"the",
"distinct",
"famous",
"release",
"dates",
"for",
"all",
"artists",
"."
] | [
{
"id": 1,
"type": "column",
"value": "famous_release_date"
},
{
"id": 0,
"type": "table",
"value": "artist"
}
] | [
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
... | [
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
528 | department_store | spider:train_spider.json:4775 | What is the largest and smallest customer codes? | SELECT max(customer_code) , min(customer_code) FROM Customers | [
"What",
"is",
"the",
"largest",
"and",
"smallest",
"customer",
"codes",
"?"
] | [
{
"id": 1,
"type": "column",
"value": "customer_code"
},
{
"id": 0,
"type": "table",
"value": "customers"
}
] | [
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"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",
"B-COLUMN",
"O"
] |
529 | debit_card_specializing | bird:dev.json:1475 | How many customers in KAM had a consumption of less than 30,000 for the year 2012? | SELECT COUNT(*) FROM ( SELECT T2.CustomerID FROM customers AS T1 INNER JOIN yearmonth AS T2 ON T1.CustomerID = T2.CustomerID WHERE T1.Segment = 'KAM' AND SUBSTRING(T2.Date, 1, 4) = '2012' GROUP BY T2.CustomerID HAVING SUM(T2.Consumption) < 30000 ) AS t1 | [
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"customers",
"in",
"KAM",
"had",
"a",
"consumption",
"of",
"less",
"than",
"30,000",
"for",
"the",
"year",
"2012",
"?"
] | [
{
"id": 7,
"type": "column",
"value": "consumption"
},
{
"id": 0,
"type": "column",
"value": "customerid"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "yearmonth"
},
{
"id": 4,
"type": "column",
... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
... | [
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"B-VALUE",
"O"
] |
530 | chinook_1 | spider:train_spider.json:890 | Find the titles of albums that contain tracks of both the Reggae and Rock genres. | SELECT T1.Title FROM Album AS T1 JOIN Track AS T2 ON T1.AlbumId = T2.AlbumId JOIN Genre AS T3 ON T2.GenreID = T3.GenreID WHERE T3.Name = 'Reggae' INTERSECT SELECT T1.Title FROM Album AS T1 JOIN Track AS T2 ON T1.AlbumId = T2.AlbumId JOIN Genre AS T3 ON T2.GenreID = T3.GenreID WHERE T3.Name = 'Rock' | [
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"titles",
"of",
"albums",
"that",
"contain",
"tracks",
"of",
"both",
"the",
"Reggae",
"and",
"Rock",
"genres",
"."
] | [
{
"id": 7,
"type": "column",
"value": "genreid"
},
{
"id": 8,
"type": "column",
"value": "albumid"
},
{
"id": 3,
"type": "value",
"value": "Reggae"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "table",
"value": "ge... | [
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"enti... | [
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
531 | talkingdata | bird:train.json:1112 | What is the brand of the youngest user's device? | SELECT device_model FROM phone_brand_device_model2 WHERE device_id IN ( SELECT device_id FROM gender_age WHERE age = ( SELECT MIN(age) FROM gender_age ) ) | [
"What",
"is",
"the",
"brand",
"of",
"the",
"youngest",
"user",
"'s",
"device",
"?"
] | [
{
"id": 0,
"type": "table",
"value": "phone_brand_device_model2"
},
{
"id": 1,
"type": "column",
"value": "device_model"
},
{
"id": 3,
"type": "table",
"value": "gender_age"
},
{
"id": 2,
"type": "column",
"value": "device_id"
},
{
"id": 4,
"ty... | [
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
... | [
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
532 | codebase_community | bird:dev.json:700 | Identify the number of posts that offer a bounty amount over 30. | SELECT COUNT(id) FROM votes WHERE BountyAmount >= 30 | [
"Identify",
"the",
"number",
"of",
"posts",
"that",
"offer",
"a",
"bounty",
"amount",
"over",
"30",
"."
] | [
{
"id": 1,
"type": "column",
"value": "bountyamount"
},
{
"id": 0,
"type": "table",
"value": "votes"
},
{
"id": 2,
"type": "value",
"value": "30"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] | [
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
8,
9
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id"... | [
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
533 | world | bird:train.json:7886 | What are the cities for country called "´Uman" in local name. | SELECT T1.Name FROM City AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.Code WHERE T2.LocalName = '´Uman' | [
"What",
"are",
"the",
"cities",
"for",
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"called",
"\"",
"´Uman",
"\"",
"in",
"local",
"name",
"."
] | [
{
"id": 5,
"type": "column",
"value": "countrycode"
},
{
"id": 3,
"type": "column",
"value": "localname"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "value",
"value": "´Uman"
},
{
"id": 0,
"type": "column",
"val... | [
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
... | [
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
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