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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which committees have delegates from both democratic party and liberal party?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Committee FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T2.Party = "Democratic" INTERSECT SELECT T1.Committee FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T2.Party = "Liberal"</SQL_QUERY> | election | SELECT T1.Committee FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T2.Party = "Democratic" INTERSECT SELECT T1.Committee FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T2.Party = "Liberal" | Which committees have delegates from both democratic party and liberal party? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the committees that have delegates both from from the democratic party and the liberal party.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Committee FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T2.Party = "Democratic" INTERSECT SELECT T1.Committee FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T2.Party = "Liberal"</SQL_QUERY> | election | SELECT T1.Committee FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T2.Party = "Democratic" INTERSECT SELECT T1.Committee FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T2.Party = "Liberal" | Find the committees that have delegates both from from the democratic party and the liberal party. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many journalists are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM journalist</SQL_QUERY> | news_report | SELECT count(*) FROM journalist | How many journalists are there? | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of journalists in ascending order of years working.</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM journalist ORDER BY Years_working ASC</SQL_QUERY> | news_report | SELECT Name FROM journalist ORDER BY Years_working ASC | List the names of journalists in ascending order of years working. | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the nationalities and ages of journalists?</question>
[SQL]:
| <SQL_QUERY>SELECT Nationality , Age FROM journalist</SQL_QUERY> | news_report | SELECT Nationality , Age FROM journalist | What are the nationalities and ages of journalists? | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of journalists from "England" or "Wales".</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM journalist WHERE Nationality = "England" OR Nationality = "Wales"</SQL_QUERY> | news_report | SELECT Name FROM journalist WHERE Nationality = "England" OR Nationality = "Wales" | Show the names of journalists from "England" or "Wales". | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average number of years spent working as a journalist?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Years_working) FROM journalist</SQL_QUERY> | news_report | SELECT avg(Years_working) FROM journalist | What is the average number of years spent working as a journalist? | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the nationality of the journalist with the largest number of years working?</question>
[SQL]:
| <SQL_QUERY>SELECT Nationality FROM journalist ORDER BY Years_working DESC LIMIT 1</SQL_QUERY> | news_report | SELECT Nationality FROM journalist ORDER BY Years_working DESC LIMIT 1 | What is the nationality of the journalist with the largest number of years working? | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the different nationalities and the number of journalists of each nationality.</question>
[SQL]:
| <SQL_QUERY>SELECT Nationality , COUNT(*) FROM journalist GROUP BY Nationality</SQL_QUERY> | news_report | SELECT Nationality , COUNT(*) FROM journalist GROUP BY Nationality | Show the different nationalities and the number of journalists of each nationality. | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the most common nationality for journalists.</question>
[SQL]:
| <SQL_QUERY>SELECT Nationality FROM journalist GROUP BY Nationality ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | news_report | SELECT Nationality FROM journalist GROUP BY Nationality ORDER BY COUNT(*) DESC LIMIT 1 | Show the most common nationality for journalists. | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the nations that have both journalists with more than 10 years of working and journalists with less than 3 years of working.</question>
[SQL]:
| <SQL_QUERY>SELECT Nationality FROM journalist WHERE Years_working > 10 INTERSECT SELECT Nationality FROM journalist WHERE Years_working < 3</SQL_QUERY> | news_report | SELECT Nationality FROM journalist WHERE Years_working > 10 INTERSECT SELECT Nationality FROM journalist WHERE Years_working < 3 | Show the nations that have both journalists with more than 10 years of working and journalists with less than 3 years of working. | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the dates, places, and names of events in descending order of the attendance.</question>
[SQL]:
| <SQL_QUERY>SELECT Date , Name , venue FROM event ORDER BY Event_Attendance DESC</SQL_QUERY> | news_report | SELECT Date , Name , venue FROM event ORDER BY Event_Attendance DESC | Show the dates, places, and names of events in descending order of the attendance. | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of journalists and the dates of the events they reported.</question>
[SQL]:
| <SQL_QUERY>SELECT T3.Name , T2.Date FROM news_report AS T1 JOIN event AS T2 ON T1.Event_ID = T2.Event_ID JOIN journalist AS T3 ON T1.journalist_ID = T3.journalist_ID</SQL_QUERY> | news_report | SELECT T3.Name , T2.Date FROM news_report AS T1 JOIN event AS T2 ON T1.Event_ID = T2.Event_ID JOIN journalist AS T3 ON T1.journalist_ID = T3.journalist_ID | Show the names of journalists and the dates of the events they reported. | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of journalists and the names of the events they reported in ascending order</question>
[SQL]:
| <SQL_QUERY>SELECT T3.Name , T2.Name FROM news_report AS T1 JOIN event AS T2 ON T1.Event_ID = T2.Event_ID JOIN journalist AS T3 ON T1.journalist_ID = T3.journalist_ID ORDER BY T2.Event_Attendance ASC</SQL_QUERY> | news_report | SELECT T3.Name , T2.Name FROM news_report AS T1 JOIN event AS T2 ON T1.Event_ID = T2.Event_ID JOIN journalist AS T3 ON T1.journalist_ID = T3.journalist_ID ORDER BY T2.Event_Attendance ASC | Show the names of journalists and the names of the events they reported in ascending order | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of journalists and the number of events they reported.</question>
[SQL]:
| <SQL_QUERY>SELECT T3.Name , COUNT(*) FROM news_report AS T1 JOIN event AS T2 ON T1.Event_ID = T2.Event_ID JOIN journalist AS T3 ON T1.journalist_ID = T3.journalist_ID GROUP BY T3.Name</SQL_QUERY> | news_report | SELECT T3.Name , COUNT(*) FROM news_report AS T1 JOIN event AS T2 ON T1.Event_ID = T2.Event_ID JOIN journalist AS T3 ON T1.journalist_ID = T3.journalist_ID GROUP BY T3.Name | Show the names of journalists and the number of events they reported. | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of journalists that have reported more than one event.</question>
[SQL]:
| <SQL_QUERY>SELECT T3.Name FROM news_report AS T1 JOIN event AS T2 ON T1.Event_ID = T2.Event_ID JOIN journalist AS T3 ON T1.journalist_ID = T3.journalist_ID GROUP BY T3.Name HAVING COUNT(*) > 1</SQL_QUERY> | news_report | SELECT T3.Name FROM news_report AS T1 JOIN event AS T2 ON T1.Event_ID = T2.Event_ID JOIN journalist AS T3 ON T1.journalist_ID = T3.journalist_ID GROUP BY T3.Name HAVING COUNT(*) > 1 | Show the names of journalists that have reported more than one event. | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of journalists who have not reported any event.</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM journalist WHERE journalist_ID NOT IN (SELECT journalist_ID FROM news_report)</SQL_QUERY> | news_report | SELECT Name FROM journalist WHERE journalist_ID NOT IN (SELECT journalist_ID FROM news_report) | List the names of journalists who have not reported any event. | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>what are the average and maximum attendances of all events?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Event_Attendance) , max(Event_Attendance) FROM event</SQL_QUERY> | news_report | SELECT avg(Event_Attendance) , max(Event_Attendance) FROM event | what are the average and maximum attendances of all events? | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the average age and experience working length of journalists working on different role type.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(t1.age) , avg(Years_working) , t2.work_type FROM journalist AS t1 JOIN news_report AS t2 ON t1.journalist_id = t2.journalist_id GROUP BY t2.work_type</SQL_QUERY> | news_report | SELECT avg(t1.age) , avg(Years_working) , t2.work_type FROM journalist AS t1 JOIN news_report AS t2 ON t1.journalist_id = t2.journalist_id GROUP BY t2.work_type | Find the average age and experience working length of journalists working on different role type. | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text);</schema>"
<primary_keys>[Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id</primary_keys>"
<foreign_keys>[Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the event venues and names that have the top 2 most number of people attended.</question>
[SQL]:
| <SQL_QUERY>SELECT venue , name FROM event ORDER BY Event_Attendance DESC LIMIT 2</SQL_QUERY> | news_report | SELECT venue , name FROM event ORDER BY Event_Attendance DESC LIMIT 2 | List the event venues and names that have the top 2 most number of people attended. | [Schema (values) (types)]: | news_report | event : event_id (text) , date (number) , venue (text) , name (text) , event_attendance (text) | journalist : journalist_id (text) , name (number) , nationality (text) , age (text) , years_working (text) | news_report : journalist_id (text) , event_id (number) , work_type (text); | [Primary Keys]: event : event_id, journalist : journalist_id, news_report : journalist_id | [Foreign Keys]: news_report : event_id = event : event_id | news_report : journalist_id = journalist : journalist_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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show me all the restaurants.</question>
[SQL]:
| <SQL_QUERY>SELECT ResName FROM Restaurant;</SQL_QUERY> | restaurant_1 | SELECT ResName FROM Restaurant; | Show me all the restaurants. | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the address of the restaurant Subway?</question>
[SQL]:
| <SQL_QUERY>SELECT Address FROM Restaurant WHERE ResName = "Subway";</SQL_QUERY> | restaurant_1 | SELECT Address FROM Restaurant WHERE ResName = "Subway"; | What is the address of the restaurant Subway? | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the rating of the restaurant Subway?</question>
[SQL]:
| <SQL_QUERY>SELECT Rating FROM Restaurant WHERE ResName = "Subway";</SQL_QUERY> | restaurant_1 | SELECT Rating FROM Restaurant WHERE ResName = "Subway"; | What is the rating of the restaurant Subway? | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>List all restaurant types.</question>
[SQL]:
| <SQL_QUERY>SELECT ResTypeName FROM Restaurant_Type;</SQL_QUERY> | restaurant_1 | SELECT ResTypeName FROM Restaurant_Type; | List all restaurant types. | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the description of the restaurant type Sandwich?</question>
[SQL]:
| <SQL_QUERY>SELECT ResTypeDescription FROM Restaurant_Type WHERE ResTypeName = "Sandwich";</SQL_QUERY> | restaurant_1 | SELECT ResTypeDescription FROM Restaurant_Type WHERE ResTypeName = "Sandwich"; | What is the description of the restaurant type Sandwich? | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which restaurants have highest rating? List the restaurant name and its rating.</question>
[SQL]:
| <SQL_QUERY>SELECT ResName , Rating FROM Restaurant ORDER BY Rating DESC LIMIT 1;</SQL_QUERY> | restaurant_1 | SELECT ResName , Rating FROM Restaurant ORDER BY Rating DESC LIMIT 1; | Which restaurants have highest rating? List the restaurant name and its rating. | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the age of student Linda Smith?</question>
[SQL]:
| <SQL_QUERY>SELECT Age FROM Student WHERE Fname = "Linda" AND Lname = "Smith";</SQL_QUERY> | restaurant_1 | SELECT Age FROM Student WHERE Fname = "Linda" AND Lname = "Smith"; | What is the age of student Linda Smith? | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the gender of the student Linda Smith?</question>
[SQL]:
| <SQL_QUERY>SELECT Sex FROM Student WHERE Fname = "Linda" AND Lname = "Smith";</SQL_QUERY> | restaurant_1 | SELECT Sex FROM Student WHERE Fname = "Linda" AND Lname = "Smith"; | What is the gender of the student Linda Smith? | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>List all students' first names and last names who majored in 600.</question>
[SQL]:
| <SQL_QUERY>SELECT Fname , Lname FROM Student WHERE Major = 600;</SQL_QUERY> | restaurant_1 | SELECT Fname , Lname FROM Student WHERE Major = 600; | List all students' first names and last names who majored in 600. | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which city does student Linda Smith live in?</question>
[SQL]:
| <SQL_QUERY>SELECT city_code FROM Student WHERE Fname = "Linda" AND Lname = "Smith";</SQL_QUERY> | restaurant_1 | SELECT city_code FROM Student WHERE Fname = "Linda" AND Lname = "Smith"; | Which city does student Linda Smith live in? | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Advisor 1121 has how many students?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM Student WHERE Advisor = 1121;</SQL_QUERY> | restaurant_1 | SELECT count(*) FROM Student WHERE Advisor = 1121; | Advisor 1121 has how many students? | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which Advisor has most of students? List advisor and the number of students.</question>
[SQL]:
| <SQL_QUERY>SELECT Advisor , count(*) FROM Student GROUP BY Advisor ORDER BY count(Advisor) DESC LIMIT 1;</SQL_QUERY> | restaurant_1 | SELECT Advisor , count(*) FROM Student GROUP BY Advisor ORDER BY count(Advisor) DESC LIMIT 1; | Which Advisor has most of students? List advisor and the number of students. | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which major has least number of students? List the major and the number of students.</question>
[SQL]:
| <SQL_QUERY>SELECT Major , count(*) FROM Student GROUP BY Major ORDER BY count(Major) ASC LIMIT 1;</SQL_QUERY> | restaurant_1 | SELECT Major , count(*) FROM Student GROUP BY Major ORDER BY count(Major) ASC LIMIT 1; | Which major has least number of students? List the major and the number of students. | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which major has between 2 and 30 number of students? List major and the number of students.</question>
[SQL]:
| <SQL_QUERY>SELECT Major , count(*) FROM Student GROUP BY Major HAVING count(Major) BETWEEN 2 AND 30;</SQL_QUERY> | restaurant_1 | SELECT Major , count(*) FROM Student GROUP BY Major HAVING count(Major) BETWEEN 2 AND 30; | Which major has between 2 and 30 number of students? List major and the number of students. | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which student's age is older than 18 and is majoring in 600? List each student's first and last name.</question>
[SQL]:
| <SQL_QUERY>SELECT Fname , Lname FROM Student WHERE Age > 18 AND Major = 600;</SQL_QUERY> | restaurant_1 | SELECT Fname , Lname FROM Student WHERE Age > 18 AND Major = 600; | Which student's age is older than 18 and is majoring in 600? List each student's first and last name. | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>List all female students age is older than 18 who is not majoring in 600. List students' first name and last name.</question>
[SQL]:
| <SQL_QUERY>SELECT Fname , Lname FROM Student WHERE Age > 18 AND Major != 600 AND Sex = 'F';</SQL_QUERY> | restaurant_1 | SELECT Fname , Lname FROM Student WHERE Age > 18 AND Major != 600 AND Sex = 'F'; | List all female students age is older than 18 who is not majoring in 600. List students' first name and last name. | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many restaurant is the Sandwich type restaurant?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM Restaurant JOIN Type_Of_Restaurant ON Restaurant.ResID = Type_Of_Restaurant.ResID JOIN Restaurant_Type ON Type_Of_Restaurant.ResTypeID = Restaurant_Type.ResTypeID GROUP BY Type_Of_Restaurant.ResTypeID HAVING Restaurant_Type.ResTypeName = 'Sandwich'</SQL_QUERY> | restaurant_1 | SELECT count(*) FROM Restaurant JOIN Type_Of_Restaurant ON Restaurant.ResID = Type_Of_Restaurant.ResID JOIN Restaurant_Type ON Type_Of_Restaurant.ResTypeID = Restaurant_Type.ResTypeID GROUP BY Type_Of_Restaurant.ResTypeID HAVING Restaurant_Type.ResTypeName = 'Sandwich' | How many restaurant is the Sandwich type restaurant? | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How long does student Linda Smith spend on the restaurant in total?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(Spent) FROM Student JOIN Visits_Restaurant ON Student.StuID = Visits_Restaurant.StuID WHERE Student.Fname = "Linda" AND Student.Lname = "Smith";</SQL_QUERY> | restaurant_1 | SELECT sum(Spent) FROM Student JOIN Visits_Restaurant ON Student.StuID = Visits_Restaurant.StuID WHERE Student.Fname = "Linda" AND Student.Lname = "Smith"; | How long does student Linda Smith spend on the restaurant in total? | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many times has the student Linda Smith visited Subway?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM Student JOIN Visits_Restaurant ON Student.StuID = Visits_Restaurant.StuID JOIN Restaurant ON Visits_Restaurant.ResID = Restaurant.ResID WHERE Student.Fname = "Linda" AND Student.Lname = "Smith" AND Restaurant.ResName = "Subway";</SQL_QUERY> | restaurant_1 | SELECT count(*) FROM Student JOIN Visits_Restaurant ON Student.StuID = Visits_Restaurant.StuID JOIN Restaurant ON Visits_Restaurant.ResID = Restaurant.ResID WHERE Student.Fname = "Linda" AND Student.Lname = "Smith" AND Restaurant.ResName = "Subway"; | How many times has the student Linda Smith visited Subway? | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>When did Linda Smith visit Subway?</question>
[SQL]:
| <SQL_QUERY>SELECT TIME FROM Student JOIN Visits_Restaurant ON Student.StuID = Visits_Restaurant.StuID JOIN Restaurant ON Visits_Restaurant.ResID = Restaurant.ResID WHERE Student.Fname = "Linda" AND Student.Lname = "Smith" AND Restaurant.ResName = "Subway";</SQL_QUERY> | restaurant_1 | SELECT TIME FROM Student JOIN Visits_Restaurant ON Student.StuID = Visits_Restaurant.StuID JOIN Restaurant ON Visits_Restaurant.ResID = Restaurant.ResID WHERE Student.Fname = "Linda" AND Student.Lname = "Smith" AND Restaurant.ResName = "Subway"; | When did Linda Smith visit Subway? | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>At which restaurant did the students spend the least amount of time? List restaurant and the time students spent on in total.</question>
[SQL]:
| <SQL_QUERY>SELECT Restaurant.ResName , sum(Visits_Restaurant.Spent) FROM Visits_Restaurant JOIN Restaurant ON Visits_Restaurant.ResID = Restaurant.ResID GROUP BY Restaurant.ResID ORDER BY sum(Visits_Restaurant.Spent) ASC LIMIT 1;</SQL_QUERY> | restaurant_1 | SELECT Restaurant.ResName , sum(Visits_Restaurant.Spent) FROM Visits_Restaurant JOIN Restaurant ON Visits_Restaurant.ResID = Restaurant.ResID GROUP BY Restaurant.ResID ORDER BY sum(Visits_Restaurant.Spent) ASC LIMIT 1; | At which restaurant did the students spend the least amount of time? List restaurant and the time students spent on in total. | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid</primary_keys>"
<foreign_keys>[Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which student visited restaurant most often? List student's first name and last name.</question>
[SQL]:
| <SQL_QUERY>SELECT Student.Fname , Student.Lname FROM Student JOIN Visits_Restaurant ON Student.StuID = Visits_Restaurant.StuID GROUP BY Student.StuID ORDER BY count(*) DESC LIMIT 1;</SQL_QUERY> | restaurant_1 | SELECT Student.Fname , Student.Lname FROM Student JOIN Visits_Restaurant ON Student.StuID = Visits_Restaurant.StuID GROUP BY Student.StuID ORDER BY count(*) DESC LIMIT 1; | Which student visited restaurant most often? List student's first name and last name. | [Schema (values) (types)]: | restaurant_1 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Restaurant : resid (text) , resname (number) , address (text) , rating (text) | Type_Of_Restaurant : resid (text) , restypeid (number) | Restaurant_Type : restypeid (text) , restypename (number) , restypedescription (text) | Visits_Restaurant : stuid (text) , resid (number) , time (text) , spent (text); | [Primary Keys]: student : stuid, restaurant : resid, type_of_restaurant : restypeid | [Foreign Keys]: type_of_restaurant : restypeid = restaurant_type : restypeid | type_of_restaurant : resid = restaurant : resid | visits_restaurant : resid = restaurant : resid | visits_restaurant : stuid = student : stuid |
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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the ids of orders whose status is 'Success'.</question>
[SQL]:
| <SQL_QUERY>SELECT actual_order_id FROM actual_orders WHERE order_status_code = 'Success'</SQL_QUERY> | customer_deliveries | SELECT actual_order_id FROM actual_orders WHERE order_status_code = 'Success' | Find the ids of orders whose status is 'Success'. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name and price of the product that has been ordered the greatest number of times.</question>
[SQL]:
| <SQL_QUERY>SELECT t1.product_name , t1.product_price FROM products AS t1 JOIN regular_order_products AS t2 ON t1.product_id = t2.product_id GROUP BY t2.product_id ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | customer_deliveries | SELECT t1.product_name , t1.product_price FROM products AS t1 JOIN regular_order_products AS t2 ON t1.product_id = t2.product_id GROUP BY t2.product_id ORDER BY count(*) DESC LIMIT 1 | Find the name and price of the product that has been ordered the greatest number of times. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of customers in total.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM customers</SQL_QUERY> | customer_deliveries | SELECT count(*) FROM customers | Find the number of customers in total. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many different payment methods are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT payment_method) FROM customers</SQL_QUERY> | customer_deliveries | SELECT count(DISTINCT payment_method) FROM customers | How many different payment methods are there? | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the details of all trucks in the order of their license number.</question>
[SQL]:
| <SQL_QUERY>SELECT truck_details FROM trucks ORDER BY truck_licence_number</SQL_QUERY> | customer_deliveries | SELECT truck_details FROM trucks ORDER BY truck_licence_number | Show the details of all trucks in the order of their license number. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of the most expensive product.</question>
[SQL]:
| <SQL_QUERY>SELECT product_name FROM products ORDER BY product_price DESC LIMIT 1</SQL_QUERY> | customer_deliveries | SELECT product_name FROM products ORDER BY product_price DESC LIMIT 1 | Find the name of the most expensive product. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the names of customers who are not living in the state of California.</question>
[SQL]:
| <SQL_QUERY>SELECT customer_name FROM customers EXCEPT SELECT t1.customer_name FROM customers AS t1 JOIN customer_addresses AS t2 ON t1.customer_id = t2.customer_id JOIN addresses AS t3 ON t2.address_id = t3.address_id WHERE t3.state_province_county = 'California'</SQL_QUERY> | customer_deliveries | SELECT customer_name FROM customers EXCEPT SELECT t1.customer_name FROM customers AS t1 JOIN customer_addresses AS t2 ON t1.customer_id = t2.customer_id JOIN addresses AS t3 ON t2.address_id = t3.address_id WHERE t3.state_province_county = 'California' | Find the names of customers who are not living in the state of California. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names and emails of customers who payed by Visa card.</question>
[SQL]:
| <SQL_QUERY>SELECT customer_email , customer_name FROM customers WHERE payment_method = 'Visa'</SQL_QUERY> | customer_deliveries | SELECT customer_email , customer_name FROM customers WHERE payment_method = 'Visa' | List the names and emails of customers who payed by Visa card. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the names and phone numbers of customers living in California state.</question>
[SQL]:
| <SQL_QUERY>SELECT t1.customer_name , t1.customer_phone FROM customers AS t1 JOIN customer_addresses AS t2 ON t1.customer_id = t2.customer_id JOIN addresses AS t3 ON t2.address_id = t3.address_id WHERE t3.state_province_county = 'California'</SQL_QUERY> | customer_deliveries | SELECT t1.customer_name , t1.customer_phone FROM customers AS t1 JOIN customer_addresses AS t2 ON t1.customer_id = t2.customer_id JOIN addresses AS t3 ON t2.address_id = t3.address_id WHERE t3.state_province_county = 'California' | Find the names and phone numbers of customers living in California state. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the states which do not have any employee in their record.</question>
[SQL]:
| <SQL_QUERY>SELECT state_province_county FROM addresses WHERE address_id NOT IN (SELECT employee_address_id FROM Employees)</SQL_QUERY> | customer_deliveries | SELECT state_province_county FROM addresses WHERE address_id NOT IN (SELECT employee_address_id FROM Employees) | Find the states which do not have any employee in their record. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names, phone numbers, and emails of all customers sorted by their dates of becoming customers.</question>
[SQL]:
| <SQL_QUERY>SELECT customer_name , customer_phone , customer_email FROM Customers ORDER BY date_became_customer</SQL_QUERY> | customer_deliveries | SELECT customer_name , customer_phone , customer_email FROM Customers ORDER BY date_became_customer | List the names, phone numbers, and emails of all customers sorted by their dates of becoming customers. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of the first 5 customers.</question>
[SQL]:
| <SQL_QUERY>SELECT customer_name FROM Customers ORDER BY date_became_customer LIMIT 5</SQL_QUERY> | customer_deliveries | SELECT customer_name FROM Customers ORDER BY date_became_customer LIMIT 5 | Find the name of the first 5 customers. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the payment method that is used most frequently.</question>
[SQL]:
| <SQL_QUERY>SELECT payment_method FROM Customers GROUP BY payment_method ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | customer_deliveries | SELECT payment_method FROM Customers GROUP BY payment_method ORDER BY count(*) DESC LIMIT 1 | Find the payment method that is used most frequently. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of all routes in alphabetic order.</question>
[SQL]:
| <SQL_QUERY>SELECT route_name FROM Delivery_Routes ORDER BY route_name</SQL_QUERY> | customer_deliveries | SELECT route_name FROM Delivery_Routes ORDER BY route_name | List the names of all routes in alphabetic order. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of route that has the highest number of deliveries.</question>
[SQL]:
| <SQL_QUERY>SELECT t1.route_name FROM Delivery_Routes AS t1 JOIN Delivery_Route_Locations AS t2 ON t1.route_id = t2.route_id GROUP BY t1.route_id ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | customer_deliveries | SELECT t1.route_name FROM Delivery_Routes AS t1 JOIN Delivery_Route_Locations AS t2 ON t1.route_id = t2.route_id GROUP BY t1.route_id ORDER BY count(*) DESC LIMIT 1 | Find the name of route that has the highest number of deliveries. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number);</schema>"
<primary_keys>[Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id</primary_keys>"
<foreign_keys>[Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the state names and the number of customers living in each state.</question>
[SQL]:
| <SQL_QUERY>SELECT t2.state_province_county , count(*) FROM customer_addresses AS t1 JOIN addresses AS t2 ON t1.address_id = t2.address_id GROUP BY t2.state_province_county</SQL_QUERY> | customer_deliveries | SELECT t2.state_province_county , count(*) FROM customer_addresses AS t1 JOIN addresses AS t2 ON t1.address_id = t2.address_id GROUP BY t2.state_province_county | List the state names and the number of customers living in each state. | [Schema (values) (types)]: | customer_deliveries | Products : product_id (text) , product_name (number) , product_price (text) , product_description (number) | Addresses : address_id (text) , address_details (number) , city (text) , zip_postcode (number) , state_province_county (text) , country (number) | Customers : customer_id (text) , payment_method (number) , customer_name (text) , customer_phone (number) , customer_email (text) , date_became_customer (number) | Regular_Orders : regular_order_id (text) , distributer_id (number) | Regular_Order_Products : regular_order_id (text) , product_id (number) | Actual_Orders : actual_order_id (text) , order_status_code (number) , regular_order_id (text) , actual_order_date (number) | Actual_Order_Products : actual_order_id (text) , product_id (number) | Customer_Addresses : customer_id (text) , address_id (number) , date_from (text) , address_type (number) , date_to (text) | Delivery_Routes : route_id (text) , route_name (number) , other_route_details (text) | Delivery_Route_Locations : location_code (text) , route_id (number) , location_address_id (text) , location_name (number) | Trucks : truck_id (text) , truck_licence_number (number) , truck_details (text) | Employees : employee_id (text) , employee_address_id (number) , employee_name (text) , employee_phone (number) | Order_Deliveries : location_code (text) , actual_order_id (number) , delivery_status_code (text) , driver_employee_id (number) , truck_id (text) , delivery_date (number); | [Primary Keys]: products : product_id, addresses : address_id, customers : customer_id, regular_orders : regular_order_id, regular_order_products : actual_order_id, actual_orders : route_id, actual_order_products : location_code, customer_addresses : truck_id, delivery_routes : employee_id | [Foreign Keys]: regular_orders : distributer_id = customers : customer_id | regular_order_products : regular_order_id = regular_orders : regular_order_id | regular_order_products : product_id = products : product_id | actual_orders : regular_order_id = regular_orders : regular_order_id | actual_order_products : actual_order_id = actual_orders : actual_order_id | actual_order_products : product_id = products : product_id | customer_addresses : address_id = addresses : address_id | customer_addresses : customer_id = customers : customer_id | delivery_route_locations : route_id = delivery_routes : route_id | delivery_route_locations : location_address_id = addresses : address_id | employees : employee_address_id = addresses : address_id | order_deliveries : driver_employee_id = employees : employee_id | order_deliveries : location_code = delivery_route_locations : location_code | order_deliveries : actual_order_id = actual_orders : actual_order_id | order_deliveries : truck_id = trucks : truck_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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many authors are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM authors</SQL_QUERY> | icfp_1 | SELECT count(*) FROM authors | How many authors are there? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of authors.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM authors</SQL_QUERY> | icfp_1 | SELECT count(*) FROM authors | Count the number of authors. | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many institutions are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM inst</SQL_QUERY> | icfp_1 | SELECT count(*) FROM inst | How many institutions are there? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of institutions.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM inst</SQL_QUERY> | icfp_1 | SELECT count(*) FROM inst | Count the number of institutions. | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many papers are published in total?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM papers</SQL_QUERY> | icfp_1 | SELECT count(*) FROM papers | How many papers are published in total? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of total papers.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM papers</SQL_QUERY> | icfp_1 | SELECT count(*) FROM papers | Count the number of total papers. | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the titles of papers published by "Jeremy Gibbons"?</question>
[SQL]:
| <SQL_QUERY>SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Jeremy" AND t1.lname = "Gibbons"</SQL_QUERY> | icfp_1 | SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Jeremy" AND t1.lname = "Gibbons" | What are the titles of papers published by "Jeremy Gibbons"? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the titles of all the papers written by "Jeremy Gibbons"</question>
[SQL]:
| <SQL_QUERY>SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Jeremy" AND t1.lname = "Gibbons"</SQL_QUERY> | icfp_1 | SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Jeremy" AND t1.lname = "Gibbons" | Find the titles of all the papers written by "Jeremy Gibbons" | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find all the papers published by "Aaron Turon".</question>
[SQL]:
| <SQL_QUERY>SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Aaron" AND t1.lname = "Turon"</SQL_QUERY> | icfp_1 | SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Aaron" AND t1.lname = "Turon" | Find all the papers published by "Aaron Turon". | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the titles of all the papers written by "Aaron Turon".</question>
[SQL]:
| <SQL_QUERY>SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Aaron" AND t1.lname = "Turon"</SQL_QUERY> | icfp_1 | SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Aaron" AND t1.lname = "Turon" | Find the titles of all the papers written by "Aaron Turon". | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many papers have "Atsushi Ohori" published?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Atsushi" AND t1.lname = "Ohori"</SQL_QUERY> | icfp_1 | SELECT count(*) FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Atsushi" AND t1.lname = "Ohori" | How many papers have "Atsushi Ohori" published? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many papers are "Atsushi Ohori" the author of?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Atsushi" AND t1.lname = "Ohori"</SQL_QUERY> | icfp_1 | SELECT count(*) FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Atsushi" AND t1.lname = "Ohori" | How many papers are "Atsushi Ohori" the author of? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of the institution that "Matthias Blume" belongs to?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT t3.name FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t1.fname = "Matthias" AND t1.lname = "Blume"</SQL_QUERY> | icfp_1 | SELECT DISTINCT t3.name FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t1.fname = "Matthias" AND t1.lname = "Blume" | What is the name of the institution that "Matthias Blume" belongs to? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which institution is the author "Matthias Blume" belong to? Give me the name of the institution.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT t3.name FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t1.fname = "Matthias" AND t1.lname = "Blume"</SQL_QUERY> | icfp_1 | SELECT DISTINCT t3.name FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t1.fname = "Matthias" AND t1.lname = "Blume" | Which institution is the author "Matthias Blume" belong to? Give me the name of the institution. | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which institution does "Katsuhiro Ueno" belong to?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT t3.name FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t1.fname = "Katsuhiro" AND t1.lname = "Ueno"</SQL_QUERY> | icfp_1 | SELECT DISTINCT t3.name FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t1.fname = "Katsuhiro" AND t1.lname = "Ueno" | Which institution does "Katsuhiro Ueno" belong to? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of the institution the author "Katsuhiro Ueno" belongs to?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT t3.name FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t1.fname = "Katsuhiro" AND t1.lname = "Ueno"</SQL_QUERY> | icfp_1 | SELECT DISTINCT t3.name FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t1.fname = "Katsuhiro" AND t1.lname = "Ueno" | What is the name of the institution the author "Katsuhiro Ueno" belongs to? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Who belong to the institution "University of Oxford"? Show the first names and last names.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "University of Oxford"</SQL_QUERY> | icfp_1 | SELECT DISTINCT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "University of Oxford" | Who belong to the institution "University of Oxford"? Show the first names and last names. | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the first names and last names of the authors whose institution affiliation is "University of Oxford".</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "University of Oxford"</SQL_QUERY> | icfp_1 | SELECT DISTINCT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "University of Oxford" | Find the first names and last names of the authors whose institution affiliation is "University of Oxford". | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which authors belong to the institution "Google"? Show the first names and last names.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Google"</SQL_QUERY> | icfp_1 | SELECT DISTINCT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Google" | Which authors belong to the institution "Google"? Show the first names and last names. | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the first names and last names of the authors whose institution affiliation is "Google".</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Google"</SQL_QUERY> | icfp_1 | SELECT DISTINCT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Google" | Find the first names and last names of the authors whose institution affiliation is "Google". | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the last names of the author of the paper titled "Binders Unbound"?</question>
[SQL]:
| <SQL_QUERY>SELECT t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t3.title = "Binders Unbound"</SQL_QUERY> | icfp_1 | SELECT t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t3.title = "Binders Unbound" | What are the last names of the author of the paper titled "Binders Unbound"? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Who is the author of the paper titled "Binders Unbound"? Give me the last name.</question>
[SQL]:
| <SQL_QUERY>SELECT t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t3.title = "Binders Unbound"</SQL_QUERY> | icfp_1 | SELECT t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t3.title = "Binders Unbound" | Who is the author of the paper titled "Binders Unbound"? Give me the last name. | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the first and last name of the author(s) who wrote the paper "Nameless, Painless".</question>
[SQL]:
| <SQL_QUERY>SELECT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t3.title = "Nameless , Painless"</SQL_QUERY> | icfp_1 | SELECT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t3.title = "Nameless , Painless" | Find the first and last name of the author(s) who wrote the paper "Nameless, Painless". | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the first and last name of the author who published the paper titled "Nameless, Painless"?</question>
[SQL]:
| <SQL_QUERY>SELECT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t3.title = "Nameless , Painless"</SQL_QUERY> | icfp_1 | SELECT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t3.title = "Nameless , Painless" | What are the first and last name of the author who published the paper titled "Nameless, Painless"? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the papers published under the institution "Indiana University"?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT t1.title FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Indiana University"</SQL_QUERY> | icfp_1 | SELECT DISTINCT t1.title FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Indiana University" | What are the papers published under the institution "Indiana University"? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the titles of the papers whose authors are from the institution "Indiana University".</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT t1.title FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Indiana University"</SQL_QUERY> | icfp_1 | SELECT DISTINCT t1.title FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Indiana University" | List the titles of the papers whose authors are from the institution "Indiana University". | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find all the papers published by the institution "Google".</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT t1.title FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Google"</SQL_QUERY> | icfp_1 | SELECT DISTINCT t1.title FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Google" | Find all the papers published by the institution "Google". | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which papers were written by authors from the institution "Google"?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT t1.title FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Google"</SQL_QUERY> | icfp_1 | SELECT DISTINCT t1.title FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Google" | Which papers were written by authors from the institution "Google"? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many papers are published by the institution "Tokohu University"?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT t1.title) FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Tokohu University"</SQL_QUERY> | icfp_1 | SELECT count(DISTINCT t1.title) FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Tokohu University" | How many papers are published by the institution "Tokohu University"? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of papers published by authors from the institution "Tokohu University".</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT t1.title) FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Tokohu University"</SQL_QUERY> | icfp_1 | SELECT count(DISTINCT t1.title) FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "Tokohu University" | Find the number of papers published by authors from the institution "Tokohu University". | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of papers published by the institution "University of Pennsylvania".</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT t1.title) FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "University of Pennsylvania"</SQL_QUERY> | icfp_1 | SELECT count(DISTINCT t1.title) FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "University of Pennsylvania" | Find the number of papers published by the institution "University of Pennsylvania". | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many papers are written by authors from the institution "University of Pennsylvania"?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT t1.title) FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "University of Pennsylvania"</SQL_QUERY> | icfp_1 | SELECT count(DISTINCT t1.title) FROM papers AS t1 JOIN authorship AS t2 ON t1.paperid = t2.paperid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "University of Pennsylvania" | How many papers are written by authors from the institution "University of Pennsylvania"? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the papers which have "Olin Shivers" as an author.</question>
[SQL]:
| <SQL_QUERY>SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Olin" AND t1.lname = "Shivers"</SQL_QUERY> | icfp_1 | SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Olin" AND t1.lname = "Shivers" | Find the papers which have "Olin Shivers" as an author. | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which papers did the author "Olin Shivers" write? Give me the paper titles.</question>
[SQL]:
| <SQL_QUERY>SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Olin" AND t1.lname = "Shivers"</SQL_QUERY> | icfp_1 | SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Olin" AND t1.lname = "Shivers" | Which papers did the author "Olin Shivers" write? Give me the paper titles. | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which papers have "Stephanie Weirich" as an author?</question>
[SQL]:
| <SQL_QUERY>SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Stephanie" AND t1.lname = "Weirich"</SQL_QUERY> | icfp_1 | SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Stephanie" AND t1.lname = "Weirich" | Which papers have "Stephanie Weirich" as an author? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the titles of the papers the author "Stephanie Weirich" wrote.</question>
[SQL]:
| <SQL_QUERY>SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Stephanie" AND t1.lname = "Weirich"</SQL_QUERY> | icfp_1 | SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Stephanie" AND t1.lname = "Weirich" | Find the titles of the papers the author "Stephanie Weirich" wrote. | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which paper is published in an institution in "USA" and have "Turon" as its second author?</question>
[SQL]:
| <SQL_QUERY>SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid JOIN inst AS t4 ON t2.instid = t4.instid WHERE t4.country = "USA" AND t2.authorder = 2 AND t1.lname = "Turon"</SQL_QUERY> | icfp_1 | SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid JOIN inst AS t4 ON t2.instid = t4.instid WHERE t4.country = "USA" AND t2.authorder = 2 AND t1.lname = "Turon" | Which paper is published in an institution in "USA" and have "Turon" as its second author? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find papers whose second author has last name "Turon" and is affiliated with an institution in the country "USA".</question>
[SQL]:
| <SQL_QUERY>SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid JOIN inst AS t4 ON t2.instid = t4.instid WHERE t4.country = "USA" AND t2.authorder = 2 AND t1.lname = "Turon"</SQL_QUERY> | icfp_1 | SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid JOIN inst AS t4 ON t2.instid = t4.instid WHERE t4.country = "USA" AND t2.authorder = 2 AND t1.lname = "Turon" | Find papers whose second author has last name "Turon" and is affiliated with an institution in the country "USA". | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the titles of papers whose first author is affiliated with an institution in the country "Japan" and has last name "Ohori"?</question>
[SQL]:
| <SQL_QUERY>SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid JOIN inst AS t4 ON t2.instid = t4.instid WHERE t4.country = "Japan" AND t2.authorder = 1 AND t1.lname = "Ohori"</SQL_QUERY> | icfp_1 | SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid JOIN inst AS t4 ON t2.instid = t4.instid WHERE t4.country = "Japan" AND t2.authorder = 1 AND t1.lname = "Ohori" | Find the titles of papers whose first author is affiliated with an institution in the country "Japan" and has last name "Ohori"? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which papers' first author is affiliated with an institution in the country "Japan" and has last name "Ohori"? Give me the titles of the papers.</question>
[SQL]:
| <SQL_QUERY>SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid JOIN inst AS t4 ON t2.instid = t4.instid WHERE t4.country = "Japan" AND t2.authorder = 1 AND t1.lname = "Ohori"</SQL_QUERY> | icfp_1 | SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid JOIN inst AS t4 ON t2.instid = t4.instid WHERE t4.country = "Japan" AND t2.authorder = 1 AND t1.lname = "Ohori" | Which papers' first author is affiliated with an institution in the country "Japan" and has last name "Ohori"? Give me the titles of the papers. | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the last name of the author that has published the most papers?</question>
[SQL]:
| <SQL_QUERY>SELECT t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid GROUP BY t1.fname , t1.lname ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | icfp_1 | SELECT t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid GROUP BY t1.fname , t1.lname ORDER BY count(*) DESC LIMIT 1 | What is the last name of the author that has published the most papers? | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text);</schema>"
<primary_keys>[Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid</primary_keys>"
<foreign_keys>[Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which author has written the most papers? Find his or her last name.</question>
[SQL]:
| <SQL_QUERY>SELECT t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid GROUP BY t1.fname , t1.lname ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | icfp_1 | SELECT t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid GROUP BY t1.fname , t1.lname ORDER BY count(*) DESC LIMIT 1 | Which author has written the most papers? Find his or her last name. | [Schema (values) (types)]: | icfp_1 | Inst : instid (text) , name (number) , country (text) | Authors : authid (text) , lname (number) , fname (text) | Papers : paperid (text) , title (number) | Authorship : authid (text) , instid (number) , paperid (text) , authorder (text); | [Primary Keys]: inst : instid, authors : authid, papers : paperid, authorship : authid | [Foreign Keys]: authorship : paperid = papers : paperid | authorship : instid = inst : instid | authorship : authid = authors : authid |
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