input stringlengths 667 7.62k | output stringlengths 41 600 | db_id stringlengths 3 31 | query stringlengths 18 577 | question stringlengths 3 224 | schema stringlengths 177 6.14k | primary_keys stringlengths 16 545 | foreign_keys stringlengths 16 1.48k |
|---|---|---|---|---|---|---|---|
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the descriptions for the aircrafts?</question>
[SQL]:
| <SQL_QUERY>SELECT Description FROM aircraft</SQL_QUERY> | aircraft | SELECT Description FROM aircraft | What are the descriptions for the aircrafts? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average number of international passengers of all airports?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(International_Passengers) FROM airport</SQL_QUERY> | aircraft | SELECT avg(International_Passengers) FROM airport | What is the average number of international passengers of all airports? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average number of international passengers for an airport?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(International_Passengers) FROM airport</SQL_QUERY> | aircraft | SELECT avg(International_Passengers) FROM airport | What is the average number of international passengers for an airport? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the number of international and domestic passengers of the airport named London "Heathrow"?</question>
[SQL]:
| <SQL_QUERY>SELECT International_Passengers , Domestic_Passengers FROM airport WHERE Airport_Name = "London Heathrow"</SQL_QUERY> | aircraft | SELECT International_Passengers , Domestic_Passengers FROM airport WHERE Airport_Name = "London Heathrow" | What are the number of international and domestic passengers of the airport named London "Heathrow"? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many international and domestic passengers are there in the airport London Heathrow?</question>
[SQL]:
| <SQL_QUERY>SELECT International_Passengers , Domestic_Passengers FROM airport WHERE Airport_Name = "London Heathrow"</SQL_QUERY> | aircraft | SELECT International_Passengers , Domestic_Passengers FROM airport WHERE Airport_Name = "London Heathrow" | How many international and domestic passengers are there in the airport London Heathrow? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the total number of Domestic Passengers of airports that contain the word "London".</question>
[SQL]:
| <SQL_QUERY>SELECT sum(Domestic_Passengers) FROM airport WHERE Airport_Name LIKE "%London%"</SQL_QUERY> | aircraft | SELECT sum(Domestic_Passengers) FROM airport WHERE Airport_Name LIKE "%London%" | What are the total number of Domestic Passengers of airports that contain the word "London". | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the total number of domestic passengers at all London airports?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(Domestic_Passengers) FROM airport WHERE Airport_Name LIKE "%London%"</SQL_QUERY> | aircraft | SELECT sum(Domestic_Passengers) FROM airport WHERE Airport_Name LIKE "%London%" | What are the total number of domestic passengers at all London airports? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the maximum and minimum number of transit passengers of all aiports.</question>
[SQL]:
| <SQL_QUERY>SELECT max(Transit_Passengers) , min(Transit_Passengers) FROM airport</SQL_QUERY> | aircraft | SELECT max(Transit_Passengers) , min(Transit_Passengers) FROM airport | What are the maximum and minimum number of transit passengers of all aiports. | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the maximum and mininum number of transit passengers for all airports?</question>
[SQL]:
| <SQL_QUERY>SELECT max(Transit_Passengers) , min(Transit_Passengers) FROM airport</SQL_QUERY> | aircraft | SELECT max(Transit_Passengers) , min(Transit_Passengers) FROM airport | What is the maximum and mininum number of transit passengers for all airports? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the name of pilots aged 25 or older?</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM pilot WHERE Age >= 25</SQL_QUERY> | aircraft | SELECT Name FROM pilot WHERE Age >= 25 | What are the name of pilots aged 25 or older? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>what is the name of every pilot who is at least 25 years old?</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM pilot WHERE Age >= 25</SQL_QUERY> | aircraft | SELECT Name FROM pilot WHERE Age >= 25 | what is the name of every pilot who is at least 25 years old? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List all pilot names in ascending alphabetical order.</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM pilot ORDER BY Name ASC</SQL_QUERY> | aircraft | SELECT Name FROM pilot ORDER BY Name ASC | List all pilot names in ascending alphabetical order. | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the pilots in alphabetical order?</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM pilot ORDER BY Name ASC</SQL_QUERY> | aircraft | SELECT Name FROM pilot ORDER BY Name ASC | What are the names of the pilots in alphabetical order? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List names of all pilot aged 30 or younger in descending alphabetical order.</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM pilot WHERE Age <= 30 ORDER BY Name DESC</SQL_QUERY> | aircraft | SELECT Name FROM pilot WHERE Age <= 30 ORDER BY Name DESC | List names of all pilot aged 30 or younger in descending alphabetical order. | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all pilots 30 years old or young in descending alphabetical order?</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM pilot WHERE Age <= 30 ORDER BY Name DESC</SQL_QUERY> | aircraft | SELECT Name FROM pilot WHERE Age <= 30 ORDER BY Name DESC | What are the names of all pilots 30 years old or young in descending alphabetical order? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Please show the names of aircrafts associated with airport with name "London Gatwick".</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Aircraft FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Airport_Name = "London Gatwick"</SQL_QUERY> | aircraft | SELECT T1.Aircraft FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Airport_Name = "London Gatwick" | Please show the names of aircrafts associated with airport with name "London Gatwick". | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all the aircrafts associated with London Gatwick airport?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Aircraft FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Airport_Name = "London Gatwick"</SQL_QUERY> | aircraft | SELECT T1.Aircraft FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Airport_Name = "London Gatwick" | What are the names of all the aircrafts associated with London Gatwick airport? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Please show the names and descriptions of aircrafts associated with airports that have a total number of passengers bigger than 10000000.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Aircraft , T1.Description FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Total_Passengers > 10000000</SQL_QUERY> | aircraft | SELECT T1.Aircraft , T1.Description FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Total_Passengers > 10000000 | Please show the names and descriptions of aircrafts associated with airports that have a total number of passengers bigger than 10000000. | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names and descriptions of aircrafts associated with an airport that has more total passengers than 10000000?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Aircraft , T1.Description FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Total_Passengers > 10000000</SQL_QUERY> | aircraft | SELECT T1.Aircraft , T1.Description FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Total_Passengers > 10000000 | What are the names and descriptions of aircrafts associated with an airport that has more total passengers than 10000000? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average total number of passengers of airports that are associated with aircraft "Robinson R-22"?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(T3.Total_Passengers) FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T1.Aircraft = "Robinson R-22"</SQL_QUERY> | aircraft | SELECT avg(T3.Total_Passengers) FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T1.Aircraft = "Robinson R-22" | What is the average total number of passengers of airports that are associated with aircraft "Robinson R-22"? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average total number of passengers for all airports that the aircraft "Robinson R-22" visits?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(T3.Total_Passengers) FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T1.Aircraft = "Robinson R-22"</SQL_QUERY> | aircraft | SELECT avg(T3.Total_Passengers) FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T1.Aircraft = "Robinson R-22" | What is the average total number of passengers for all airports that the aircraft "Robinson R-22" visits? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Please list the location and the winning aircraft name.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Location , T1.Aircraft FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft</SQL_QUERY> | aircraft | SELECT T2.Location , T1.Aircraft FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft | Please list the location and the winning aircraft name. | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the location and name of the winning aircraft?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Location , T1.Aircraft FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft</SQL_QUERY> | aircraft | SELECT T2.Location , T1.Aircraft FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft | What is the location and name of the winning aircraft? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name of the aircraft that has been named winning aircraft the most number of times.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Aircraft FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | aircraft | SELECT T1.Aircraft FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft ORDER BY COUNT(*) DESC LIMIT 1 | List the name of the aircraft that has been named winning aircraft the most number of times. | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of the aircraft that has won an award the most?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Aircraft FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | aircraft | SELECT T1.Aircraft FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft ORDER BY COUNT(*) DESC LIMIT 1 | What is the name of the aircraft that has won an award the most? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of aircrafts and the number of times it won matches.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Aircraft , COUNT(*) FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft</SQL_QUERY> | aircraft | SELECT T1.Aircraft , COUNT(*) FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft | List the names of aircrafts and the number of times it won matches. | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each aircraft that has won an award, what is its name and how many time has it won?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Aircraft , COUNT(*) FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft</SQL_QUERY> | aircraft | SELECT T1.Aircraft , COUNT(*) FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft | For each aircraft that has won an award, what is its name and how many time has it won? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List names of all pilot in descending order of age.</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM pilot ORDER BY Age DESC</SQL_QUERY> | aircraft | SELECT Name FROM pilot ORDER BY Age DESC | List names of all pilot in descending order of age. | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all pilots listed by descending age?</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM pilot ORDER BY Age DESC</SQL_QUERY> | aircraft | SELECT Name FROM pilot ORDER BY Age DESC | What are the names of all pilots listed by descending age? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of aircrafts and that won matches at least twice.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Aircraft FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft HAVING COUNT(*) >= 2</SQL_QUERY> | aircraft | SELECT T1.Aircraft FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft HAVING COUNT(*) >= 2 | List the names of aircrafts and that won matches at least twice. | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all aircrafts that have won a match at least twice?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Aircraft FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft HAVING COUNT(*) >= 2</SQL_QUERY> | aircraft | SELECT T1.Aircraft FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft HAVING COUNT(*) >= 2 | What are the names of all aircrafts that have won a match at least twice? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of aircrafts and that did not win any match.</question>
[SQL]:
| <SQL_QUERY>SELECT Aircraft FROM aircraft WHERE Aircraft_ID NOT IN (SELECT Winning_Aircraft FROM MATCH)</SQL_QUERY> | aircraft | SELECT Aircraft FROM aircraft WHERE Aircraft_ID NOT IN (SELECT Winning_Aircraft FROM MATCH) | List the names of aircrafts and that did not win any match. | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all aicrafts that have never won any match?</question>
[SQL]:
| <SQL_QUERY>SELECT Aircraft FROM aircraft WHERE Aircraft_ID NOT IN (SELECT Winning_Aircraft FROM MATCH)</SQL_QUERY> | aircraft | SELECT Aircraft FROM aircraft WHERE Aircraft_ID NOT IN (SELECT Winning_Aircraft FROM MATCH) | What are the names of all aicrafts that have never won any match? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of aircrafts that are associated with both an airport named "London Heathrow" and an airport named "London Gatwick"</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Aircraft FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Airport_Name = "London Heathrow" INTERSECT SELECT T1.Aircraft FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Airport_Name = "London Gatwick"</SQL_QUERY> | aircraft | SELECT T1.Aircraft FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Airport_Name = "London Heathrow" INTERSECT SELECT T1.Aircraft FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Airport_Name = "London Gatwick" | Show the names of aircrafts that are associated with both an airport named "London Heathrow" and an airport named "London Gatwick" | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all aircrafts that are associated with both London Heathrow and Gatwick airports?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Aircraft FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Airport_Name = "London Heathrow" INTERSECT SELECT T1.Aircraft FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Airport_Name = "London Gatwick"</SQL_QUERY> | aircraft | SELECT T1.Aircraft FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Airport_Name = "London Heathrow" INTERSECT SELECT T1.Aircraft FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T3.Airport_Name = "London Gatwick" | What are the names of all aircrafts that are associated with both London Heathrow and Gatwick airports? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all information on the airport that has the largest number of international passengers.</question>
[SQL]:
| <SQL_QUERY>SELECT * FROM airport ORDER BY International_Passengers DESC LIMIT 1</SQL_QUERY> | aircraft | SELECT * FROM airport ORDER BY International_Passengers DESC LIMIT 1 | Show all information on the airport that has the largest number of international passengers. | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is all the information on the airport with the largest number of international passengers?</question>
[SQL]:
| <SQL_QUERY>SELECT * FROM airport ORDER BY International_Passengers DESC LIMIT 1</SQL_QUERY> | aircraft | SELECT * FROM airport ORDER BY International_Passengers DESC LIMIT 1 | What is all the information on the airport with the largest number of international passengers? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>find the name and age of the pilot who has won the most number of times among the pilots who are younger than 30.</question>
[SQL]:
| <SQL_QUERY>SELECT t1.name , t1.age FROM pilot AS t1 JOIN MATCH AS t2 ON t1.pilot_id = t2.winning_pilot WHERE t1.age < 30 GROUP BY t2.winning_pilot ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | aircraft | SELECT t1.name , t1.age FROM pilot AS t1 JOIN MATCH AS t2 ON t1.pilot_id = t2.winning_pilot WHERE t1.age < 30 GROUP BY t2.winning_pilot ORDER BY count(*) DESC LIMIT 1 | find the name and age of the pilot who has won the most number of times among the pilots who are younger than 30. | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name and age of the pilot younger than 30 who has won the most number of times?</question>
[SQL]:
| <SQL_QUERY>SELECT t1.name , t1.age FROM pilot AS t1 JOIN MATCH AS t2 ON t1.pilot_id = t2.winning_pilot WHERE t1.age < 30 GROUP BY t2.winning_pilot ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | aircraft | SELECT t1.name , t1.age FROM pilot AS t1 JOIN MATCH AS t2 ON t1.pilot_id = t2.winning_pilot WHERE t1.age < 30 GROUP BY t2.winning_pilot ORDER BY count(*) DESC LIMIT 1 | What is the name and age of the pilot younger than 30 who has won the most number of times? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>what is the name and age of the youngest winning pilot?</question>
[SQL]:
| <SQL_QUERY>SELECT t1.name , t1.age FROM pilot AS t1 JOIN MATCH AS t2 ON t1.pilot_id = t2.winning_pilot ORDER BY t1.age LIMIT 1</SQL_QUERY> | aircraft | SELECT t1.name , t1.age FROM pilot AS t1 JOIN MATCH AS t2 ON t1.pilot_id = t2.winning_pilot ORDER BY t1.age LIMIT 1 | what is the name and age of the youngest winning pilot? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How old is the youngest winning pilot and what is their name?</question>
[SQL]:
| <SQL_QUERY>SELECT t1.name , t1.age FROM pilot AS t1 JOIN MATCH AS t2 ON t1.pilot_id = t2.winning_pilot ORDER BY t1.age LIMIT 1</SQL_QUERY> | aircraft | SELECT t1.name , t1.age FROM pilot AS t1 JOIN MATCH AS t2 ON t1.pilot_id = t2.winning_pilot ORDER BY t1.age LIMIT 1 | How old is the youngest winning pilot and what is their name? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>find the name of pilots who did not win the matches held in the country of Australia.</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM pilot WHERE pilot_id NOT IN (SELECT Winning_Pilot FROM MATCH WHERE country = 'Australia')</SQL_QUERY> | aircraft | SELECT name FROM pilot WHERE pilot_id NOT IN (SELECT Winning_Pilot FROM MATCH WHERE country = 'Australia') | find the name of pilots who did not win the matches held in the country of Australia. | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text);</schema>"
<primary_keys>[Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id</primary_keys>"
<foreign_keys>[Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the pilots that have not won any matches in Australia?</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM pilot WHERE pilot_id NOT IN (SELECT Winning_Pilot FROM MATCH WHERE country = 'Australia')</SQL_QUERY> | aircraft | SELECT name FROM pilot WHERE pilot_id NOT IN (SELECT Winning_Pilot FROM MATCH WHERE country = 'Australia') | What are the names of the pilots that have not won any matches in Australia? | [Schema (values) (types)]: | aircraft | pilot : pilot_id (text) , name (number) , age (text) | aircraft : aircraft_id (text) , aircraft (number) , description (text) , max_gross_weight (number) , total_disk_area (number) , max_disk_loading (text) | match : round (text) , location (number) , country (text) , date (number) , fastest_qualifying (number) , winning_pilot (text) , winning_aircraft (text) | airport : airport_id (text) , airport_name (number) , total_passengers (text) , %_change_2007 (number) , international_passengers (number) , domestic_passengers (text) , transit_passengers (text) , aircraft_movements (text) , freight_metric_tonnes (text) | airport_aircraft : id (text) , airport_id (number) , aircraft_id (text); | [Primary Keys]: pilot : pilot_id, aircraft : aircraft_id, match : round, airport : airport_id, airport_aircraft : airport_id | [Foreign Keys]: match : winning_pilot = pilot : pilot_id | match : winning_aircraft = aircraft : aircraft_id | airport_aircraft : aircraft_id = aircraft : aircraft_id | airport_aircraft : airport_id = airport : airport_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many residents does each property have? List property id and resident count.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.property_id , count(*) FROM properties AS T1 JOIN residents AS T2 ON T1.property_id = T2.property_id GROUP BY T1.property_id</SQL_QUERY> | local_govt_and_lot | SELECT T1.property_id , count(*) FROM properties AS T1 JOIN residents AS T2 ON T1.property_id = T2.property_id GROUP BY T1.property_id | How many residents does each property have? List property id and resident count. | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the distinct service types that are provided by the organization which has detail 'Denesik and Sons Party'?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.service_type_code FROM services AS T1 JOIN organizations AS T2 ON T1.organization_id = T2.organization_id WHERE T2.organization_details = 'Denesik and Sons Party'</SQL_QUERY> | local_govt_and_lot | SELECT DISTINCT T1.service_type_code FROM services AS T1 JOIN organizations AS T2 ON T1.organization_id = T2.organization_id WHERE T2.organization_details = 'Denesik and Sons Party' | What is the distinct service types that are provided by the organization which has detail 'Denesik and Sons Party'? | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many services has each resident requested? List the resident id, details, and the count in descending order of the count.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.resident_id , T1.other_details , count(*) FROM Residents AS T1 JOIN Residents_Services AS T2 ON T1.resident_id = T2.resident_id GROUP BY T1.resident_id ORDER BY count(*) DESC</SQL_QUERY> | local_govt_and_lot | SELECT T1.resident_id , T1.other_details , count(*) FROM Residents AS T1 JOIN Residents_Services AS T2 ON T1.resident_id = T2.resident_id GROUP BY T1.resident_id ORDER BY count(*) DESC | How many services has each resident requested? List the resident id, details, and the count in descending order of the count. | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the maximum number that a certain service is provided? List the service id, details and number.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.service_id , T1.service_details , count(*) FROM Services AS T1 JOIN Residents_Services AS T2 ON T1.service_id = T2.service_id GROUP BY T1.service_id ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | local_govt_and_lot | SELECT T1.service_id , T1.service_details , count(*) FROM Services AS T1 JOIN Residents_Services AS T2 ON T1.service_id = T2.service_id GROUP BY T1.service_id ORDER BY count(*) DESC LIMIT 1 | What is the maximum number that a certain service is provided? List the service id, details and number. | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the id and type of each thing, and the details of the organization that owns it.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.thing_id , T1.type_of_Thing_Code , T2.organization_details FROM Things AS T1 JOIN Organizations AS T2 ON T1.organization_id = T2.organization_id</SQL_QUERY> | local_govt_and_lot | SELECT T1.thing_id , T1.type_of_Thing_Code , T2.organization_details FROM Things AS T1 JOIN Organizations AS T2 ON T1.organization_id = T2.organization_id | List the id and type of each thing, and the details of the organization that owns it. | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the id and details of the customers who have at least 3 events?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.customer_id , T1.customer_details FROM Customers AS T1 JOIN Customer_Events AS T2 ON T1.customer_id = T2.customer_id GROUP BY T1.customer_id HAVING count(*) >= 3</SQL_QUERY> | local_govt_and_lot | SELECT T1.customer_id , T1.customer_details FROM Customers AS T1 JOIN Customer_Events AS T2 ON T1.customer_id = T2.customer_id GROUP BY T1.customer_id HAVING count(*) >= 3 | What are the id and details of the customers who have at least 3 events? | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is each customer's move in date, and the corresponding customer id and details?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.date_moved_in , T1.customer_id , T1.customer_details FROM Customers AS T1 JOIN Customer_Events AS T2 ON T1.customer_id = T2.customer_id</SQL_QUERY> | local_govt_and_lot | SELECT T2.date_moved_in , T1.customer_id , T1.customer_details FROM Customers AS T1 JOIN Customer_Events AS T2 ON T1.customer_id = T2.customer_id | What is each customer's move in date, and the corresponding customer id and details? | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which events have the number of notes between one and three? List the event id and the property id.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Customer_Event_ID , T1.property_id FROM Customer_Events AS T1 JOIN Customer_Event_Notes AS T2 ON T1.Customer_Event_ID = T2.Customer_Event_ID GROUP BY T1.customer_event_id HAVING count(*) BETWEEN 1 AND 3</SQL_QUERY> | local_govt_and_lot | SELECT T1.Customer_Event_ID , T1.property_id FROM Customer_Events AS T1 JOIN Customer_Event_Notes AS T2 ON T1.Customer_Event_ID = T2.Customer_Event_ID GROUP BY T1.customer_event_id HAVING count(*) BETWEEN 1 AND 3 | Which events have the number of notes between one and three? List the event id and the property id. | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct id and type of the thing that has the status 'Close' or has a status record before the date '2017-06-19 02:59:21'</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T2.thing_id , T2.Type_of_Thing_Code FROM Timed_Status_of_Things AS T1 JOIN Things AS T2 ON T1.thing_id = T2.thing_id WHERE T1.Status_of_Thing_Code = 'Close' OR T1.Date_and_Date < '2017-06-19 02:59:21'</SQL_QUERY> | local_govt_and_lot | SELECT DISTINCT T2.thing_id , T2.Type_of_Thing_Code FROM Timed_Status_of_Things AS T1 JOIN Things AS T2 ON T1.thing_id = T2.thing_id WHERE T1.Status_of_Thing_Code = 'Close' OR T1.Date_and_Date < '2017-06-19 02:59:21' | What are the distinct id and type of the thing that has the status 'Close' or has a status record before the date '2017-06-19 02:59:21' | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many distinct locations have the things with service detail 'Unsatisfied' been located in?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT T2.Location_Code) FROM Things AS T1 JOIN Timed_Locations_of_Things AS T2 ON T1.thing_id = T2.thing_id WHERE T1.service_details = 'Unsatisfied'</SQL_QUERY> | local_govt_and_lot | SELECT count(DISTINCT T2.Location_Code) FROM Things AS T1 JOIN Timed_Locations_of_Things AS T2 ON T1.thing_id = T2.thing_id WHERE T1.service_details = 'Unsatisfied' | How many distinct locations have the things with service detail 'Unsatisfied' been located in? | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many different status codes of things are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT Status_of_Thing_Code) FROM Timed_Status_of_Things</SQL_QUERY> | local_govt_and_lot | SELECT count(DISTINCT Status_of_Thing_Code) FROM Timed_Status_of_Things | How many different status codes of things are there? | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which organizations are not a parent organization of others? List the organization id.</question>
[SQL]:
| <SQL_QUERY>SELECT organization_id FROM organizations EXCEPT SELECT parent_organization_id FROM organizations</SQL_QUERY> | local_govt_and_lot | SELECT organization_id FROM organizations EXCEPT SELECT parent_organization_id FROM organizations | Which organizations are not a parent organization of others? List the organization id. | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>When is the last day any resident moved in?</question>
[SQL]:
| <SQL_QUERY>SELECT max(date_moved_in) FROM Residents</SQL_QUERY> | local_govt_and_lot | SELECT max(date_moved_in) FROM Residents | When is the last day any resident moved in? | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the resident details containing the substring 'Miss'?</question>
[SQL]:
| <SQL_QUERY>SELECT other_details FROM Residents WHERE other_details LIKE '%Miss%'</SQL_QUERY> | local_govt_and_lot | SELECT other_details FROM Residents WHERE other_details LIKE '%Miss%' | What are the resident details containing the substring 'Miss'? | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the customer event id and the corresponding move in date and property id.</question>
[SQL]:
| <SQL_QUERY>SELECT customer_event_id , date_moved_in , property_id FROM customer_events</SQL_QUERY> | local_govt_and_lot | SELECT customer_event_id , date_moved_in , property_id FROM customer_events | List the customer event id and the corresponding move in date and property id. | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many customers did not have any event?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM customers WHERE customer_id NOT IN ( SELECT customer_id FROM customer_events )</SQL_QUERY> | local_govt_and_lot | SELECT count(*) FROM customers WHERE customer_id NOT IN ( SELECT customer_id FROM customer_events ) | How many customers did not have any event? | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text);</schema>"
<primary_keys>[Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id</primary_keys>"
<foreign_keys>[Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct move in dates of the residents?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT date_moved_in FROM residents</SQL_QUERY> | local_govt_and_lot | SELECT DISTINCT date_moved_in FROM residents | What are the distinct move in dates of the residents? | [Schema (values) (types)]: | local_govt_and_lot | Customers : customer_id (text) , customer_details (number) | Properties : property_id (text) , property_type_code (number) , property_address (text) , other_details (number) | Residents : resident_id (text) , property_id (number) , date_moved_in (text) , date_moved_out (number) , other_details (text) | Organizations : organization_id (text) , parent_organization_id (number) , organization_details (text) | Services : service_id (text) , organization_id (number) , service_type_code (text) , service_details (number) | Residents_Services : resident_id (text) , service_id (number) , date_moved_in (text) , property_id (number) , date_requested (text) , date_provided (text) , other_details (text) | Things : thing_id (text) , organization_id (number) , type_of_thing_code (text) , service_type_code (number) , service_details (text) | Customer_Events : customer_event_id (text) , customer_id (number) , date_moved_in (text) , property_id (number) , resident_id (text) , thing_id (text) | Customer_Event_Notes : customer_event_note_id (text) , customer_event_id (number) , service_type_code (text) , resident_id (number) , property_id (text) , date_moved_in (text) | Timed_Status_of_Things : thing_id (text) , date_and_date (number) , status_of_thing_code (text) | Timed_Locations_of_Things : thing_id (text) , date_and_time (number) , location_code (text); | [Primary Keys]: customers : customer_id, properties : property_id, residents : resident_id, organizations : organization_id, services : service_id, residents_services : resident_id, things : thing_id, customer_events : customer_event_id, customer_event_notes : customer_event_note_id, timed_status_of_things : thing_id, timed_locations_of_things : thing_id | [Foreign Keys]: residents : property_id = properties : property_id | services : organization_id = organizations : organization_id | residents_services : resident_id = residents : resident_id | residents_services : property_id = residents : property_id | residents_services : date_moved_in = residents : date_moved_in | residents_services : service_id = services : service_id | things : organization_id = organizations : organization_id | customer_events : resident_id = residents : resident_id | customer_events : property_id = residents : property_id | customer_events : date_moved_in = residents : date_moved_in | customer_events : customer_id = customers : customer_id | customer_events : thing_id = things : thing_id | customer_event_notes : customer_event_id = customer_events : customer_event_id | timed_status_of_things : thing_id = things : thing_id | timed_locations_of_things : thing_id = things : thing_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many schools are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM school</SQL_QUERY> | school_player | SELECT count(*) FROM school | How many schools are there? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of schools.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM school</SQL_QUERY> | school_player | SELECT count(*) FROM school | Count the number of schools. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the locations of schools in ascending order of enrollment.</question>
[SQL]:
| <SQL_QUERY>SELECT LOCATION FROM school ORDER BY Enrollment ASC</SQL_QUERY> | school_player | SELECT LOCATION FROM school ORDER BY Enrollment ASC | List the locations of schools in ascending order of enrollment. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the list of school locations sorted in ascending order of school enrollment?</question>
[SQL]:
| <SQL_QUERY>SELECT LOCATION FROM school ORDER BY Enrollment ASC</SQL_QUERY> | school_player | SELECT LOCATION FROM school ORDER BY Enrollment ASC | What is the list of school locations sorted in ascending order of school enrollment? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the locations of schools in descending order of founded year.</question>
[SQL]:
| <SQL_QUERY>SELECT LOCATION FROM school ORDER BY Founded DESC</SQL_QUERY> | school_player | SELECT LOCATION FROM school ORDER BY Founded DESC | List the locations of schools in descending order of founded year. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the list of school locations sorted in descending order of school foundation year?</question>
[SQL]:
| <SQL_QUERY>SELECT LOCATION FROM school ORDER BY Founded DESC</SQL_QUERY> | school_player | SELECT LOCATION FROM school ORDER BY Founded DESC | What is the list of school locations sorted in descending order of school foundation year? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the enrollments of schools whose denomination is not "Catholic"?</question>
[SQL]:
| <SQL_QUERY>SELECT Enrollment FROM school WHERE Denomination != "Catholic"</SQL_QUERY> | school_player | SELECT Enrollment FROM school WHERE Denomination != "Catholic" | What are the enrollments of schools whose denomination is not "Catholic"? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the enrollment for each school that does not have "Catholic" as denomination.</question>
[SQL]:
| <SQL_QUERY>SELECT Enrollment FROM school WHERE Denomination != "Catholic"</SQL_QUERY> | school_player | SELECT Enrollment FROM school WHERE Denomination != "Catholic" | List the enrollment for each school that does not have "Catholic" as denomination. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average enrollment of schools?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Enrollment) FROM school</SQL_QUERY> | school_player | SELECT avg(Enrollment) FROM school | What is the average enrollment of schools? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Take the average of the school enrollment.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Enrollment) FROM school</SQL_QUERY> | school_player | SELECT avg(Enrollment) FROM school | Take the average of the school enrollment. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the teams of the players, sorted in ascending alphabetical order?</question>
[SQL]:
| <SQL_QUERY>SELECT Team FROM player ORDER BY Team ASC</SQL_QUERY> | school_player | SELECT Team FROM player ORDER BY Team ASC | What are the teams of the players, sorted in ascending alphabetical order? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the team of each player and sort them in ascending alphabetical order.</question>
[SQL]:
| <SQL_QUERY>SELECT Team FROM player ORDER BY Team ASC</SQL_QUERY> | school_player | SELECT Team FROM player ORDER BY Team ASC | Find the team of each player and sort them in ascending alphabetical order. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many different positions of players are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT POSITION) FROM player</SQL_QUERY> | school_player | SELECT count(DISTINCT POSITION) FROM player | How many different positions of players are there? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of distinct player positions.</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT POSITION) FROM player</SQL_QUERY> | school_player | SELECT count(DISTINCT POSITION) FROM player | Count the number of distinct player positions. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the team of the player of the highest age.</question>
[SQL]:
| <SQL_QUERY>SELECT Team FROM player ORDER BY Age DESC LIMIT 1</SQL_QUERY> | school_player | SELECT Team FROM player ORDER BY Age DESC LIMIT 1 | Find the team of the player of the highest age. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which team has the oldest player?</question>
[SQL]:
| <SQL_QUERY>SELECT Team FROM player ORDER BY Age DESC LIMIT 1</SQL_QUERY> | school_player | SELECT Team FROM player ORDER BY Age DESC LIMIT 1 | Which team has the oldest player? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the teams of the players with the top 5 largest ages.</question>
[SQL]:
| <SQL_QUERY>SELECT Team FROM player ORDER BY Age DESC LIMIT 5</SQL_QUERY> | school_player | SELECT Team FROM player ORDER BY Age DESC LIMIT 5 | List the teams of the players with the top 5 largest ages. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the teams that have the 5 oldest players?</question>
[SQL]:
| <SQL_QUERY>SELECT Team FROM player ORDER BY Age DESC LIMIT 5</SQL_QUERY> | school_player | SELECT Team FROM player ORDER BY Age DESC LIMIT 5 | What are the teams that have the 5 oldest players? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each player, show the team and the location of school they belong to.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Team , T2.Location FROM player AS T1 JOIN school AS T2 ON T1.School_ID = T2.School_ID</SQL_QUERY> | school_player | SELECT T1.Team , T2.Location FROM player AS T1 JOIN school AS T2 ON T1.School_ID = T2.School_ID | For each player, show the team and the location of school they belong to. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the team and the location of school each player belongs to?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Team , T2.Location FROM player AS T1 JOIN school AS T2 ON T1.School_ID = T2.School_ID</SQL_QUERY> | school_player | SELECT T1.Team , T2.Location FROM player AS T1 JOIN school AS T2 ON T1.School_ID = T2.School_ID | What are the team and the location of school each player belongs to? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the locations of schools that have more than 1 player.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Location FROM player AS T1 JOIN school AS T2 ON T1.School_ID = T2.School_ID GROUP BY T1.School_ID HAVING COUNT(*) > 1</SQL_QUERY> | school_player | SELECT T2.Location FROM player AS T1 JOIN school AS T2 ON T1.School_ID = T2.School_ID GROUP BY T1.School_ID HAVING COUNT(*) > 1 | Show the locations of schools that have more than 1 player. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which schools have more than 1 player? Give me the school locations.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Location FROM player AS T1 JOIN school AS T2 ON T1.School_ID = T2.School_ID GROUP BY T1.School_ID HAVING COUNT(*) > 1</SQL_QUERY> | school_player | SELECT T2.Location FROM player AS T1 JOIN school AS T2 ON T1.School_ID = T2.School_ID GROUP BY T1.School_ID HAVING COUNT(*) > 1 | Which schools have more than 1 player? Give me the school locations. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the denomination of the school that has the most players.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Denomination FROM player AS T1 JOIN school AS T2 ON T1.School_ID = T2.School_ID GROUP BY T1.School_ID ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | school_player | SELECT T2.Denomination FROM player AS T1 JOIN school AS T2 ON T1.School_ID = T2.School_ID GROUP BY T1.School_ID ORDER BY COUNT(*) DESC LIMIT 1 | Show the denomination of the school that has the most players. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the denomination of the school the most players belong to?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Denomination FROM player AS T1 JOIN school AS T2 ON T1.School_ID = T2.School_ID GROUP BY T1.School_ID ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | school_player | SELECT T2.Denomination FROM player AS T1 JOIN school AS T2 ON T1.School_ID = T2.School_ID GROUP BY T1.School_ID ORDER BY COUNT(*) DESC LIMIT 1 | What is the denomination of the school the most players belong to? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show locations and nicknames of schools.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Location , T2.Nickname FROM school AS T1 JOIN school_details AS T2 ON T1.School_ID = T2.School_ID</SQL_QUERY> | school_player | SELECT T1.Location , T2.Nickname FROM school AS T1 JOIN school_details AS T2 ON T1.School_ID = T2.School_ID | Show locations and nicknames of schools. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the location and nickname of each school?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Location , T2.Nickname FROM school AS T1 JOIN school_details AS T2 ON T1.School_ID = T2.School_ID</SQL_QUERY> | school_player | SELECT T1.Location , T2.Nickname FROM school AS T1 JOIN school_details AS T2 ON T1.School_ID = T2.School_ID | What are the location and nickname of each school? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Please show different denominations and the corresponding number of schools.</question>
[SQL]:
| <SQL_QUERY>SELECT Denomination , COUNT(*) FROM school GROUP BY Denomination</SQL_QUERY> | school_player | SELECT Denomination , COUNT(*) FROM school GROUP BY Denomination | Please show different denominations and the corresponding number of schools. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each denomination, return the denomination and the count of schools with that denomination.</question>
[SQL]:
| <SQL_QUERY>SELECT Denomination , COUNT(*) FROM school GROUP BY Denomination</SQL_QUERY> | school_player | SELECT Denomination , COUNT(*) FROM school GROUP BY Denomination | For each denomination, return the denomination and the count of schools with that denomination. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Please show different denominations and the corresponding number of schools in descending order.</question>
[SQL]:
| <SQL_QUERY>SELECT Denomination , COUNT(*) FROM school GROUP BY Denomination ORDER BY COUNT(*) DESC</SQL_QUERY> | school_player | SELECT Denomination , COUNT(*) FROM school GROUP BY Denomination ORDER BY COUNT(*) DESC | Please show different denominations and the corresponding number of schools in descending order. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Order denominations in descending order of the count of schools with the denomination. Return each denomination with the count of schools.</question>
[SQL]:
| <SQL_QUERY>SELECT Denomination , COUNT(*) FROM school GROUP BY Denomination ORDER BY COUNT(*) DESC</SQL_QUERY> | school_player | SELECT Denomination , COUNT(*) FROM school GROUP BY Denomination ORDER BY COUNT(*) DESC | Order denominations in descending order of the count of schools with the denomination. Return each denomination with the count of schools. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the school color of the school that has the largest enrollment.</question>
[SQL]:
| <SQL_QUERY>SELECT School_Colors FROM school ORDER BY Enrollment DESC LIMIT 1</SQL_QUERY> | school_player | SELECT School_Colors FROM school ORDER BY Enrollment DESC LIMIT 1 | List the school color of the school that has the largest enrollment. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the school color of the school with the largest enrollment?</question>
[SQL]:
| <SQL_QUERY>SELECT School_Colors FROM school ORDER BY Enrollment DESC LIMIT 1</SQL_QUERY> | school_player | SELECT School_Colors FROM school ORDER BY Enrollment DESC LIMIT 1 | What is the school color of the school with the largest enrollment? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the locations of schools that do not have any player.</question>
[SQL]:
| <SQL_QUERY>SELECT LOCATION FROM school WHERE School_ID NOT IN (SELECT School_ID FROM Player)</SQL_QUERY> | school_player | SELECT LOCATION FROM school WHERE School_ID NOT IN (SELECT School_ID FROM Player) | List the locations of schools that do not have any player. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which schools do not have any player? Give me the school locations.</question>
[SQL]:
| <SQL_QUERY>SELECT LOCATION FROM school WHERE School_ID NOT IN (SELECT School_ID FROM Player)</SQL_QUERY> | school_player | SELECT LOCATION FROM school WHERE School_ID NOT IN (SELECT School_ID FROM Player) | Which schools do not have any player? Give me the school locations. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the denomination shared by schools founded before 1890 and schools founded after 1900</question>
[SQL]:
| <SQL_QUERY>SELECT Denomination FROM school WHERE Founded < 1890 INTERSECT SELECT Denomination FROM school WHERE Founded > 1900</SQL_QUERY> | school_player | SELECT Denomination FROM school WHERE Founded < 1890 INTERSECT SELECT Denomination FROM school WHERE Founded > 1900 | Show the denomination shared by schools founded before 1890 and schools founded after 1900 | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the denominations used by both schools founded before 1890 and schools founded after 1900?</question>
[SQL]:
| <SQL_QUERY>SELECT Denomination FROM school WHERE Founded < 1890 INTERSECT SELECT Denomination FROM school WHERE Founded > 1900</SQL_QUERY> | school_player | SELECT Denomination FROM school WHERE Founded < 1890 INTERSECT SELECT Denomination FROM school WHERE Founded > 1900 | What are the denominations used by both schools founded before 1890 and schools founded after 1900? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the nicknames of schools that are not in division 1.</question>
[SQL]:
| <SQL_QUERY>SELECT Nickname FROM school_details WHERE Division != "Division 1"</SQL_QUERY> | school_player | SELECT Nickname FROM school_details WHERE Division != "Division 1" | Show the nicknames of schools that are not in division 1. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the nicknames of schools whose division is not 1?</question>
[SQL]:
| <SQL_QUERY>SELECT Nickname FROM school_details WHERE Division != "Division 1"</SQL_QUERY> | school_player | SELECT Nickname FROM school_details WHERE Division != "Division 1" | What are the nicknames of schools whose division is not 1? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the denomination shared by more than one school.</question>
[SQL]:
| <SQL_QUERY>SELECT Denomination FROM school GROUP BY Denomination HAVING COUNT(*) > 1</SQL_QUERY> | school_player | SELECT Denomination FROM school GROUP BY Denomination HAVING COUNT(*) > 1 | Show the denomination shared by more than one school. | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number);</schema>"
<primary_keys>[Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id</primary_keys>"
<foreign_keys>[Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the denomination more than one school have?</question>
[SQL]:
| <SQL_QUERY>SELECT Denomination FROM school GROUP BY Denomination HAVING COUNT(*) > 1</SQL_QUERY> | school_player | SELECT Denomination FROM school GROUP BY Denomination HAVING COUNT(*) > 1 | What are the denomination more than one school have? | [Schema (values) (types)]: | school_player | school : school_id (text) , school (number) , location (text) , enrollment (text) , founded (number) , denomination (number) , boys_or_girls (text) , day_or_boarding (text) , year_entered_competition (text) , school_colors (number) | school_details : school_id (text) , nickname (number) , colors (text) , league (text) , class (number) , division (number) | school_performance : school_id (text) , school_year (number) , class_a (text) , class_aa (text) | player : player_id (text) , player (number) , team (text) , age (text) , position (number) , school_id (number); | [Primary Keys]: school : school_id, school_details : school_id, school_performance : school_id, player : player_id | [Foreign Keys]: school_details : school_id = school : school_id | school_performance : school_id = school : school_id | player : school_id = school : school_id |
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