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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the names and total checking and savings balances of accounts whose savings balance is higher than the average savings balance.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T2.balance + T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T3.balance > (SELECT avg(balance) FROM savings)</SQL_QUERY> | small_bank_1 | SELECT T1.name , T2.balance + T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T3.balance > (SELECT avg(balance) FROM savings) | Find the names and total checking and savings balances of accounts whose savings balance is higher than the average savings balance. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names and sum of checking and savings balances for accounts with savings balances higher than the average savings balance?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T2.balance + T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T3.balance > (SELECT avg(balance) FROM savings)</SQL_QUERY> | small_bank_1 | SELECT T1.name , T2.balance + T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T3.balance > (SELECT avg(balance) FROM savings) | What are the names and sum of checking and savings balances for accounts with savings balances higher than the average savings balance? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name and checking balance of the account with the lowest savings balance.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T3.balance LIMIT 1</SQL_QUERY> | small_bank_1 | SELECT T1.name , T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T3.balance LIMIT 1 | Find the name and checking balance of the account with the lowest savings balance. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names and balances of checking accounts belonging to the customer with the lowest savings balance?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T3.balance LIMIT 1</SQL_QUERY> | small_bank_1 | SELECT T1.name , T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T3.balance LIMIT 1 | What are the names and balances of checking accounts belonging to the customer with the lowest savings balance? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of checking accounts for each account name.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid GROUP BY T1.name</SQL_QUERY> | small_bank_1 | SELECT count(*) , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid GROUP BY T1.name | Find the number of checking accounts for each account name. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of customers with accounts, and how many checking accounts do each of them have?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid GROUP BY T1.name</SQL_QUERY> | small_bank_1 | SELECT count(*) , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid GROUP BY T1.name | What are the names of customers with accounts, and how many checking accounts do each of them have? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the total saving balance for each account name.</question>
[SQL]:
| <SQL_QUERY>SELECT sum(T2.balance) , T1.name FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid GROUP BY T1.name</SQL_QUERY> | small_bank_1 | SELECT sum(T2.balance) , T1.name FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid GROUP BY T1.name | Find the total saving balance for each account name. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of customers with accounts, and what are the total savings balances for each?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(T2.balance) , T1.name FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid GROUP BY T1.name</SQL_QUERY> | small_bank_1 | SELECT sum(T2.balance) , T1.name FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid GROUP BY T1.name | What are the names of customers with accounts, and what are the total savings balances for each? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of accounts whose checking balance is below the average checking balance.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T2.balance < (SELECT avg(balance) FROM checking)</SQL_QUERY> | small_bank_1 | SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T2.balance < (SELECT avg(balance) FROM checking) | Find the name of accounts whose checking balance is below the average checking balance. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of customers with checking balances lower than the average checking balance?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T2.balance < (SELECT avg(balance) FROM checking)</SQL_QUERY> | small_bank_1 | SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T2.balance < (SELECT avg(balance) FROM checking) | What are the names of customers with checking balances lower than the average checking balance? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the saving balance of the account with the highest checking balance.</question>
[SQL]:
| <SQL_QUERY>SELECT T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T2.balance DESC LIMIT 1</SQL_QUERY> | small_bank_1 | SELECT T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T2.balance DESC LIMIT 1 | Find the saving balance of the account with the highest checking balance. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the savings balance of the account belonging to the customer with the highest checking balance?</question>
[SQL]:
| <SQL_QUERY>SELECT T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T2.balance DESC LIMIT 1</SQL_QUERY> | small_bank_1 | SELECT T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T2.balance DESC LIMIT 1 | What is the savings balance of the account belonging to the customer with the highest checking balance? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the total checking and saving balance of all accounts sorted by the total balance in ascending order.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.balance + T2.balance FROM checking AS T1 JOIN savings AS T2 ON T1.custid = T2.custid ORDER BY T1.balance + T2.balance</SQL_QUERY> | small_bank_1 | SELECT T1.balance + T2.balance FROM checking AS T1 JOIN savings AS T2 ON T1.custid = T2.custid ORDER BY T1.balance + T2.balance | Find the total checking and saving balance of all accounts sorted by the total balance in ascending order. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the sum of checking and savings balances for all customers, ordered by the total balance?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.balance + T2.balance FROM checking AS T1 JOIN savings AS T2 ON T1.custid = T2.custid ORDER BY T1.balance + T2.balance</SQL_QUERY> | small_bank_1 | SELECT T1.balance + T2.balance FROM checking AS T1 JOIN savings AS T2 ON T1.custid = T2.custid ORDER BY T1.balance + T2.balance | What is the sum of checking and savings balances for all customers, ordered by the total balance? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name and checking balance of the account with the lowest saving balance.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.balance , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T3.balance LIMIT 1</SQL_QUERY> | small_bank_1 | SELECT T2.balance , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T3.balance LIMIT 1 | Find the name and checking balance of the account with the lowest saving balance. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name and checking balance of the account which has the lowest savings balance?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.balance , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T3.balance LIMIT 1</SQL_QUERY> | small_bank_1 | SELECT T2.balance , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T3.balance LIMIT 1 | What is the name and checking balance of the account which has the lowest savings balance? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name, checking balance and saving balance of all accounts in the bank.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.balance , T3.balance , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid</SQL_QUERY> | small_bank_1 | SELECT T2.balance , T3.balance , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid | Find the name, checking balance and saving balance of all accounts in the bank. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names, checking balances, and savings balances for all customers?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.balance , T3.balance , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid</SQL_QUERY> | small_bank_1 | SELECT T2.balance , T3.balance , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid | What are the names, checking balances, and savings balances for all customers? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name, checking balance and savings balance of all accounts in the bank sorted by their total checking and savings balance in descending order.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.balance , T3.balance , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T2.balance + T3.balance DESC</SQL_QUERY> | small_bank_1 | SELECT T2.balance , T3.balance , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T2.balance + T3.balance DESC | Find the name, checking balance and savings balance of all accounts in the bank sorted by their total checking and savings balance in descending order. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names, checking balances, and savings balances of customers, ordered by the total of checking and savings balances descending?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.balance , T3.balance , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T2.balance + T3.balance DESC</SQL_QUERY> | small_bank_1 | SELECT T2.balance , T3.balance , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T2.balance + T3.balance DESC | What are the names, checking balances, and savings balances of customers, ordered by the total of checking and savings balances descending? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of accounts whose checking balance is higher than corresponding saving balance.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T2.balance > T3.balance</SQL_QUERY> | small_bank_1 | SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T2.balance > T3.balance | Find the name of accounts whose checking balance is higher than corresponding saving balance. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of customers with a higher checking balance than savings balance?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T2.balance > T3.balance</SQL_QUERY> | small_bank_1 | SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T2.balance > T3.balance | What are the names of customers with a higher checking balance than savings balance? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name and total checking and savings balance of the accounts whose savings balance is lower than corresponding checking balance.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T3.balance + T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T3.balance < T2.balance</SQL_QUERY> | small_bank_1 | SELECT T1.name , T3.balance + T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T3.balance < T2.balance | Find the name and total checking and savings balance of the accounts whose savings balance is lower than corresponding checking balance. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of customers who have a savings balance lower than their checking balance, and what is the total of their checking and savings balances?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T3.balance + T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T3.balance < T2.balance</SQL_QUERY> | small_bank_1 | SELECT T1.name , T3.balance + T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T3.balance < T2.balance | What are the names of customers who have a savings balance lower than their checking balance, and what is the total of their checking and savings balances? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name and savings balance of the top 3 accounts with the highest saving balance sorted by savings balance in descending order.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T2.balance FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid ORDER BY T2.balance DESC LIMIT 3</SQL_QUERY> | small_bank_1 | SELECT T1.name , T2.balance FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid ORDER BY T2.balance DESC LIMIT 3 | Find the name and savings balance of the top 3 accounts with the highest saving balance sorted by savings balance in descending order. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are names and savings balances of the three accounts with the highest savings balances?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T2.balance FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid ORDER BY T2.balance DESC LIMIT 3</SQL_QUERY> | small_bank_1 | SELECT T1.name , T2.balance FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid ORDER BY T2.balance DESC LIMIT 3 | What are names and savings balances of the three accounts with the highest savings balances? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many main stream browsers whose market share is at least 5 exist?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM browser WHERE market_share >= 5</SQL_QUERY> | browser_web | SELECT count(*) FROM browser WHERE market_share >= 5 | How many main stream browsers whose market share is at least 5 exist? | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name of browsers in descending order by market share.</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM browser ORDER BY market_share DESC</SQL_QUERY> | browser_web | SELECT name FROM browser ORDER BY market_share DESC | List the name of browsers in descending order by market share. | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the ids, names and market shares of all browsers.</question>
[SQL]:
| <SQL_QUERY>SELECT id , name , market_share FROM browser</SQL_QUERY> | browser_web | SELECT id , name , market_share FROM browser | List the ids, names and market shares of all browsers. | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the maximum, minimum and average market share of the listed browsers?</question>
[SQL]:
| <SQL_QUERY>SELECT max(market_share) , min(market_share) , avg(market_share) FROM browser</SQL_QUERY> | browser_web | SELECT max(market_share) , min(market_share) , avg(market_share) FROM browser | What is the maximum, minimum and average market share of the listed browsers? | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the id and market share of the browser Safari?</question>
[SQL]:
| <SQL_QUERY>SELECT id , market_share FROM browser WHERE name = 'Safari'</SQL_QUERY> | browser_web | SELECT id , market_share FROM browser WHERE name = 'Safari' | What is the id and market share of the browser Safari? | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the name and os of web client accelerators that do not work with only a 'Broadband' type connection?</question>
[SQL]:
| <SQL_QUERY>SELECT name , operating_system FROM web_client_accelerator WHERE CONNECTION != 'Broadband'</SQL_QUERY> | browser_web | SELECT name , operating_system FROM web_client_accelerator WHERE CONNECTION != 'Broadband' | What are the name and os of web client accelerators that do not work with only a 'Broadband' type connection? | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of the browser that became compatible with the accelerator 'CProxy' after year 1998 ?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM browser AS T1 JOIN accelerator_compatible_browser AS T2 ON T1.id = T2.browser_id JOIN web_client_accelerator AS T3 ON T2.accelerator_id = T3.id WHERE T3.name = 'CProxy' AND T2.compatible_since_year > 1998</SQL_QUERY> | browser_web | SELECT T1.name FROM browser AS T1 JOIN accelerator_compatible_browser AS T2 ON T1.id = T2.browser_id JOIN web_client_accelerator AS T3 ON T2.accelerator_id = T3.id WHERE T3.name = 'CProxy' AND T2.compatible_since_year > 1998 | What is the name of the browser that became compatible with the accelerator 'CProxy' after year 1998 ? | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the ids and names of the web accelerators that are compatible with two or more browsers?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.id , T1.Name FROM web_client_accelerator AS T1 JOIN accelerator_compatible_browser AS T2 ON T2.accelerator_id = T1.id GROUP BY T1.id HAVING count(*) >= 2</SQL_QUERY> | browser_web | SELECT T1.id , T1.Name FROM web_client_accelerator AS T1 JOIN accelerator_compatible_browser AS T2 ON T2.accelerator_id = T1.id GROUP BY T1.id HAVING count(*) >= 2 | What are the ids and names of the web accelerators that are compatible with two or more browsers? | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the id and name of the browser that is compatible with the most web accelerators?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.id , T1.name FROM browser AS T1 JOIN accelerator_compatible_browser AS T2 ON T1.id = T2.browser_id GROUP BY T1.id ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | browser_web | SELECT T1.id , T1.name FROM browser AS T1 JOIN accelerator_compatible_browser AS T2 ON T1.id = T2.browser_id GROUP BY T1.id ORDER BY count(*) DESC LIMIT 1 | What is the id and name of the browser that is compatible with the most web accelerators? | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>When did the web accelerator 'CACHEbox' and browser 'Internet Explorer' become compatible?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.compatible_since_year FROM accelerator_compatible_browser AS T1 JOIN browser AS T2 ON T1.browser_id = T2.id JOIN web_client_accelerator AS T3 ON T1.accelerator_id = T3.id WHERE T3.name = 'CACHEbox' AND T2.name = 'Internet Explorer'</SQL_QUERY> | browser_web | SELECT T1.compatible_since_year FROM accelerator_compatible_browser AS T1 JOIN browser AS T2 ON T1.browser_id = T2.id JOIN web_client_accelerator AS T3 ON T1.accelerator_id = T3.id WHERE T3.name = 'CACHEbox' AND T2.name = 'Internet Explorer' | When did the web accelerator 'CACHEbox' and browser 'Internet Explorer' become compatible? | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many different kinds of clients are supported by the web clients accelerators?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT client) FROM web_client_accelerator</SQL_QUERY> | browser_web | SELECT count(DISTINCT client) FROM web_client_accelerator | How many different kinds of clients are supported by the web clients accelerators? | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many accelerators are not compatible with the browsers listed ?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM web_client_accelerator WHERE id NOT IN ( SELECT accelerator_id FROM accelerator_compatible_browser );</SQL_QUERY> | browser_web | SELECT count(*) FROM web_client_accelerator WHERE id NOT IN ( SELECT accelerator_id FROM accelerator_compatible_browser ); | How many accelerators are not compatible with the browsers listed ? | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What distinct accelerator names are compatible with the browswers that have market share higher than 15?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.name FROM web_client_accelerator AS T1 JOIN accelerator_compatible_browser AS T2 ON T2.accelerator_id = T1.id JOIN browser AS T3 ON T2.browser_id = T3.id WHERE T3.market_share > 15;</SQL_QUERY> | browser_web | SELECT DISTINCT T1.name FROM web_client_accelerator AS T1 JOIN accelerator_compatible_browser AS T2 ON T2.accelerator_id = T1.id JOIN browser AS T3 ON T2.browser_id = T3.id WHERE T3.market_share > 15; | What distinct accelerator names are compatible with the browswers that have market share higher than 15? | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of the browser that are compatible with both 'CACHEbox' and 'Fasterfox'.</question>
[SQL]:
| <SQL_QUERY>SELECT T3.name FROM web_client_accelerator AS T1 JOIN accelerator_compatible_browser AS T2 ON T2.accelerator_id = T1.id JOIN browser AS T3 ON T2.browser_id = T3.id WHERE T1.name = 'CACHEbox' INTERSECT SELECT T3.name FROM web_client_accelerator AS T1 JOIN accelerator_compatible_browser AS T2 ON T2.accelerator_id = T1.id JOIN browser AS T3 ON T2.browser_id = T3.id WHERE T1.name = 'Fasterfox'</SQL_QUERY> | browser_web | SELECT T3.name FROM web_client_accelerator AS T1 JOIN accelerator_compatible_browser AS T2 ON T2.accelerator_id = T1.id JOIN browser AS T3 ON T2.browser_id = T3.id WHERE T1.name = 'CACHEbox' INTERSECT SELECT T3.name FROM web_client_accelerator AS T1 JOIN accelerator_compatible_browser AS T2 ON T2.accelerator_id = T1.id JOIN browser AS T3 ON T2.browser_id = T3.id WHERE T1.name = 'Fasterfox' | List the names of the browser that are compatible with both 'CACHEbox' and 'Fasterfox'. | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the accelerator names and supporting operating systems that are not compatible with the browser named 'Opera'.</question>
[SQL]:
| <SQL_QUERY>SELECT name , operating_system FROM web_client_accelerator EXCEPT SELECT T1.name , T1.operating_system FROM web_client_accelerator AS T1 JOIN accelerator_compatible_browser AS T2 ON T2.accelerator_id = T1.id JOIN browser AS T3 ON T2.browser_id = T3.id WHERE T3.name = 'Opera'</SQL_QUERY> | browser_web | SELECT name , operating_system FROM web_client_accelerator EXCEPT SELECT T1.name , T1.operating_system FROM web_client_accelerator AS T1 JOIN accelerator_compatible_browser AS T2 ON T2.accelerator_id = T1.id JOIN browser AS T3 ON T2.browser_id = T3.id WHERE T3.name = 'Opera' | Show the accelerator names and supporting operating systems that are not compatible with the browser named 'Opera'. | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which accelerator name contains substring "Opera"?</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM web_client_accelerator WHERE name LIKE "%Opera%"</SQL_QUERY> | browser_web | SELECT name FROM web_client_accelerator WHERE name LIKE "%Opera%" | Which accelerator name contains substring "Opera"? | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of web accelerators used for each Operating system.</question>
[SQL]:
| <SQL_QUERY>SELECT Operating_system , count(*) FROM web_client_accelerator GROUP BY Operating_system</SQL_QUERY> | browser_web | SELECT Operating_system , count(*) FROM web_client_accelerator GROUP BY Operating_system | Find the number of web accelerators used for each Operating system. | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text);</schema>"
<primary_keys>[Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id</primary_keys>"
<foreign_keys>[Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>give me names of all compatible browsers and accelerators in the descending order of compatible year</question>
[SQL]:
| <SQL_QUERY>SELECT T2.name , T3.name FROM accelerator_compatible_browser AS T1 JOIN browser AS T2 ON T1.browser_id = T2.id JOIN web_client_accelerator AS T3 ON T1.accelerator_id = T3.id ORDER BY T1.compatible_since_year DESC</SQL_QUERY> | browser_web | SELECT T2.name , T3.name FROM accelerator_compatible_browser AS T1 JOIN browser AS T2 ON T1.browser_id = T2.id JOIN web_client_accelerator AS T3 ON T1.accelerator_id = T3.id ORDER BY T1.compatible_since_year DESC | give me names of all compatible browsers and accelerators in the descending order of compatible year | [Schema (values) (types)]: | browser_web | Web_client_accelerator : id (text) , name (number) , operating_system (text) , client (text) , connection (text) | browser : id (text) , name (number) , market_share (text) | accelerator_compatible_browser : accelerator_id (text) , browser_id (number) , compatible_since_year (text); | [Primary Keys]: web_client_accelerator : id, browser : id, accelerator_compatible_browser : accelerator_id | [Foreign Keys]: accelerator_compatible_browser : browser_id = browser : id | accelerator_compatible_browser : accelerator_id = web_client_accelerator : 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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many wrestlers are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM wrestler</SQL_QUERY> | wrestler | SELECT count(*) FROM wrestler | How many wrestlers are there? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of wrestlers.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM wrestler</SQL_QUERY> | wrestler | SELECT count(*) FROM wrestler | Count the number of wrestlers. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of wrestlers in descending order of days held.</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM wrestler ORDER BY Days_held DESC</SQL_QUERY> | wrestler | SELECT Name FROM wrestler ORDER BY Days_held DESC | List the names of wrestlers in descending order of days held. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the wrestlers, ordered descending by days held?</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM wrestler ORDER BY Days_held DESC</SQL_QUERY> | wrestler | SELECT Name FROM wrestler ORDER BY Days_held DESC | What are the names of the wrestlers, ordered descending by days held? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of the wrestler with the fewest days held?</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM wrestler ORDER BY Days_held ASC LIMIT 1</SQL_QUERY> | wrestler | SELECT Name FROM wrestler ORDER BY Days_held ASC LIMIT 1 | What is the name of the wrestler with the fewest days held? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the name of the wrestler who had the lowest number of days held.</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM wrestler ORDER BY Days_held ASC LIMIT 1</SQL_QUERY> | wrestler | SELECT Name FROM wrestler ORDER BY Days_held ASC LIMIT 1 | Return the name of the wrestler who had the lowest number of days held. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct reigns of wrestlers whose location is not "Tokyo,Japan" ?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT Reign FROM wrestler WHERE LOCATION != "Tokyo , Japan"</SQL_QUERY> | wrestler | SELECT DISTINCT Reign FROM wrestler WHERE LOCATION != "Tokyo , Japan" | What are the distinct reigns of wrestlers whose location is not "Tokyo,Japan" ? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Give the different reigns of wrestlers who are not located in Tokyo, Japan.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT Reign FROM wrestler WHERE LOCATION != "Tokyo , Japan"</SQL_QUERY> | wrestler | SELECT DISTINCT Reign FROM wrestler WHERE LOCATION != "Tokyo , Japan" | Give the different reigns of wrestlers who are not located in Tokyo, Japan. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names and location of the wrestlers?</question>
[SQL]:
| <SQL_QUERY>SELECT Name , LOCATION FROM wrestler</SQL_QUERY> | wrestler | SELECT Name , LOCATION FROM wrestler | What are the names and location of the wrestlers? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Give the names and locations of all wrestlers.</question>
[SQL]:
| <SQL_QUERY>SELECT Name , LOCATION FROM wrestler</SQL_QUERY> | wrestler | SELECT Name , LOCATION FROM wrestler | Give the names and locations of all wrestlers. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the elimination moves of wrestlers whose team is "Team Orton"?</question>
[SQL]:
| <SQL_QUERY>SELECT Elimination_Move FROM Elimination WHERE Team = "Team Orton"</SQL_QUERY> | wrestler | SELECT Elimination_Move FROM Elimination WHERE Team = "Team Orton" | What are the elimination moves of wrestlers whose team is "Team Orton"? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the elimination movies of wrestlers on Team Orton.</question>
[SQL]:
| <SQL_QUERY>SELECT Elimination_Move FROM Elimination WHERE Team = "Team Orton"</SQL_QUERY> | wrestler | SELECT Elimination_Move FROM Elimination WHERE Team = "Team Orton" | Return the elimination movies of wrestlers on Team Orton. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of wrestlers and the elimination moves?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Name , T1.Elimination_Move FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID</SQL_QUERY> | wrestler | SELECT T2.Name , T1.Elimination_Move FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID | What are the names of wrestlers and the elimination moves? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Give the names of wrestlers and their elimination moves.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Name , T1.Elimination_Move FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID</SQL_QUERY> | wrestler | SELECT T2.Name , T1.Elimination_Move FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID | Give the names of wrestlers and their elimination moves. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of wrestlers and the teams in elimination in descending order of days held.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Name , T1.Team FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID ORDER BY T2.Days_held DESC</SQL_QUERY> | wrestler | SELECT T2.Name , T1.Team FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID ORDER BY T2.Days_held DESC | List the names of wrestlers and the teams in elimination in descending order of days held. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of wrestlers and their teams in elimination, ordered descending by days held?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Name , T1.Team FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID ORDER BY T2.Days_held DESC</SQL_QUERY> | wrestler | SELECT T2.Name , T1.Team FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID ORDER BY T2.Days_held DESC | What are the names of wrestlers and their teams in elimination, ordered descending by days held? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the time of elimination of the wrestlers with largest days held.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Time FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID ORDER BY T2.Days_held DESC LIMIT 1</SQL_QUERY> | wrestler | SELECT T1.Time FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID ORDER BY T2.Days_held DESC LIMIT 1 | List the time of elimination of the wrestlers with largest days held. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the time of elimination for the wrestler with the most days held?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Time FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID ORDER BY T2.Days_held DESC LIMIT 1</SQL_QUERY> | wrestler | SELECT T1.Time FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID ORDER BY T2.Days_held DESC LIMIT 1 | What is the time of elimination for the wrestler with the most days held? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show times of elimination of wrestlers with days held more than 50.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Time FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID WHERE T2.Days_held > 50</SQL_QUERY> | wrestler | SELECT T1.Time FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID WHERE T2.Days_held > 50 | Show times of elimination of wrestlers with days held more than 50. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the times of elimination for wrestlers with over 50 days held?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Time FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID WHERE T2.Days_held > 50</SQL_QUERY> | wrestler | SELECT T1.Time FROM elimination AS T1 JOIN wrestler AS T2 ON T1.Wrestler_ID = T2.Wrestler_ID WHERE T2.Days_held > 50 | What are the times of elimination for wrestlers with over 50 days held? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show different teams in eliminations and the number of eliminations from each team.</question>
[SQL]:
| <SQL_QUERY>SELECT Team , COUNT(*) FROM elimination GROUP BY Team</SQL_QUERY> | wrestler | SELECT Team , COUNT(*) FROM elimination GROUP BY Team | Show different teams in eliminations and the number of eliminations from each team. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many eliminations did each team have?</question>
[SQL]:
| <SQL_QUERY>SELECT Team , COUNT(*) FROM elimination GROUP BY Team</SQL_QUERY> | wrestler | SELECT Team , COUNT(*) FROM elimination GROUP BY Team | How many eliminations did each team have? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show teams that have suffered more than three eliminations.</question>
[SQL]:
| <SQL_QUERY>SELECT Team FROM elimination GROUP BY Team HAVING COUNT(*) > 3</SQL_QUERY> | wrestler | SELECT Team FROM elimination GROUP BY Team HAVING COUNT(*) > 3 | Show teams that have suffered more than three eliminations. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which teams had more than 3 eliminations?</question>
[SQL]:
| <SQL_QUERY>SELECT Team FROM elimination GROUP BY Team HAVING COUNT(*) > 3</SQL_QUERY> | wrestler | SELECT Team FROM elimination GROUP BY Team HAVING COUNT(*) > 3 | Which teams had more than 3 eliminations? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the reign and days held of wrestlers.</question>
[SQL]:
| <SQL_QUERY>SELECT Reign , Days_held FROM wrestler</SQL_QUERY> | wrestler | SELECT Reign , Days_held FROM wrestler | Show the reign and days held of wrestlers. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the reigns and days held of all wrestlers?</question>
[SQL]:
| <SQL_QUERY>SELECT Reign , Days_held FROM wrestler</SQL_QUERY> | wrestler | SELECT Reign , Days_held FROM wrestler | What are the reigns and days held of all wrestlers? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of wrestlers days held less than 100?</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM wrestler WHERE Days_held < 100</SQL_QUERY> | wrestler | SELECT Name FROM wrestler WHERE Days_held < 100 | What are the names of wrestlers days held less than 100? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the names of wrestlers with fewer than 100 days held.</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM wrestler WHERE Days_held < 100</SQL_QUERY> | wrestler | SELECT Name FROM wrestler WHERE Days_held < 100 | Return the names of wrestlers with fewer than 100 days held. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Please show the most common reigns of wrestlers.</question>
[SQL]:
| <SQL_QUERY>SELECT Reign FROM wrestler GROUP BY Reign ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | wrestler | SELECT Reign FROM wrestler GROUP BY Reign ORDER BY COUNT(*) DESC LIMIT 1 | Please show the most common reigns of wrestlers. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which reign is the most common among wrestlers?</question>
[SQL]:
| <SQL_QUERY>SELECT Reign FROM wrestler GROUP BY Reign ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | wrestler | SELECT Reign FROM wrestler GROUP BY Reign ORDER BY COUNT(*) DESC LIMIT 1 | Which reign is the most common among wrestlers? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the locations that are shared by more than two wrestlers.</question>
[SQL]:
| <SQL_QUERY>SELECT LOCATION FROM wrestler GROUP BY LOCATION HAVING COUNT(*) > 2</SQL_QUERY> | wrestler | SELECT LOCATION FROM wrestler GROUP BY LOCATION HAVING COUNT(*) > 2 | List the locations that are shared by more than two wrestlers. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which locations are shared by more than two wrestlers?</question>
[SQL]:
| <SQL_QUERY>SELECT LOCATION FROM wrestler GROUP BY LOCATION HAVING COUNT(*) > 2</SQL_QUERY> | wrestler | SELECT LOCATION FROM wrestler GROUP BY LOCATION HAVING COUNT(*) > 2 | Which locations are shared by more than two wrestlers? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of wrestlers that have not been eliminated.</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM wrestler WHERE Wrestler_ID NOT IN (SELECT Wrestler_ID FROM elimination)</SQL_QUERY> | wrestler | SELECT Name FROM wrestler WHERE Wrestler_ID NOT IN (SELECT Wrestler_ID FROM elimination) | List the names of wrestlers that have not been eliminated. | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of wrestlers who have never been eliminated?</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM wrestler WHERE Wrestler_ID NOT IN (SELECT Wrestler_ID FROM elimination)</SQL_QUERY> | wrestler | SELECT Name FROM wrestler WHERE Wrestler_ID NOT IN (SELECT Wrestler_ID FROM elimination) | What are the names of wrestlers who have never been eliminated? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the teams that have both wrestlers eliminated by "Orton" and wrestlers eliminated by "Benjamin".</question>
[SQL]:
| <SQL_QUERY>SELECT Team FROM Elimination WHERE Eliminated_By = "Orton" INTERSECT SELECT Team FROM Elimination WHERE Eliminated_By = "Benjamin"</SQL_QUERY> | wrestler | SELECT Team FROM Elimination WHERE Eliminated_By = "Orton" INTERSECT SELECT Team FROM Elimination WHERE Eliminated_By = "Benjamin" | Show the teams that have both wrestlers eliminated by "Orton" and wrestlers eliminated by "Benjamin". | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the teams that have both wrestlers eliminated by Orton and wrestlers eliminated by Benjamin?</question>
[SQL]:
| <SQL_QUERY>SELECT Team FROM Elimination WHERE Eliminated_By = "Orton" INTERSECT SELECT Team FROM Elimination WHERE Eliminated_By = "Benjamin"</SQL_QUERY> | wrestler | SELECT Team FROM Elimination WHERE Eliminated_By = "Orton" INTERSECT SELECT Team FROM Elimination WHERE Eliminated_By = "Benjamin" | What are the teams that have both wrestlers eliminated by Orton and wrestlers eliminated by Benjamin? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the number of distinct teams that suffer elimination?</question>
[SQL]:
| <SQL_QUERY>SELECT COUNT (DISTINCT team) FROM elimination</SQL_QUERY> | wrestler | SELECT COUNT (DISTINCT team) FROM elimination | What is the number of distinct teams that suffer elimination? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many different teams have had eliminated wrestlers?</question>
[SQL]:
| <SQL_QUERY>SELECT COUNT (DISTINCT team) FROM elimination</SQL_QUERY> | wrestler | SELECT COUNT (DISTINCT team) FROM elimination | How many different teams have had eliminated wrestlers? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the times of elimination by "Punk" or "Orton".</question>
[SQL]:
| <SQL_QUERY>SELECT TIME FROM elimination WHERE Eliminated_By = "Punk" OR Eliminated_By = "Orton"</SQL_QUERY> | wrestler | SELECT TIME FROM elimination WHERE Eliminated_By = "Punk" OR Eliminated_By = "Orton" | Show the times of elimination by "Punk" or "Orton". | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_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)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text);</schema>"
<primary_keys>[Primary Keys]: wrestler : wrestler_id, elimination : elimination_id</primary_keys>"
<foreign_keys>[Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the times of elimination for any instances in which the elimination was done by Punk or Orton?</question>
[SQL]:
| <SQL_QUERY>SELECT TIME FROM elimination WHERE Eliminated_By = "Punk" OR Eliminated_By = "Orton"</SQL_QUERY> | wrestler | SELECT TIME FROM elimination WHERE Eliminated_By = "Punk" OR Eliminated_By = "Orton" | What are the times of elimination for any instances in which the elimination was done by Punk or Orton? | [Schema (values) (types)]: | wrestler | wrestler : wrestler_id (text) , name (number) , reign (text) , days_held (text) , location (text) , event (text) | Elimination : elimination_id (text) , wrestler_id (number) , team (text) , eliminated_by (text) , elimination_move (text) , time (text); | [Primary Keys]: wrestler : wrestler_id, elimination : elimination_id | [Foreign Keys]: elimination : wrestler_id = wrestler : wrestler_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many schools are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM school</SQL_QUERY> | school_finance | SELECT count(*) FROM school | How many schools are there? | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of schools.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM school</SQL_QUERY> | school_finance | SELECT count(*) FROM school | Count the number of schools. | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all school names in alphabetical order.</question>
[SQL]:
| <SQL_QUERY>SELECT school_name FROM school ORDER BY school_name</SQL_QUERY> | school_finance | SELECT school_name FROM school ORDER BY school_name | Show all school names in alphabetical order. | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name, location, mascot for all schools.</question>
[SQL]:
| <SQL_QUERY>SELECT school_name , LOCATION , mascot FROM school</SQL_QUERY> | school_finance | SELECT school_name , LOCATION , mascot FROM school | List the name, location, mascot for all schools. | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the total and average enrollment of all schools?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(enrollment) , avg(enrollment) FROM school</SQL_QUERY> | school_finance | SELECT sum(enrollment) , avg(enrollment) FROM school | What are the total and average enrollment of all schools? | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the mascots for schools with enrollments above the average?</question>
[SQL]:
| <SQL_QUERY>SELECT mascot FROM school WHERE enrollment > (SELECT avg(enrollment) FROM school)</SQL_QUERY> | school_finance | SELECT mascot FROM school WHERE enrollment > (SELECT avg(enrollment) FROM school) | What are the mascots for schools with enrollments above the average? | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name of the school with the smallest enrollment.</question>
[SQL]:
| <SQL_QUERY>SELECT school_name FROM school ORDER BY enrollment LIMIT 1</SQL_QUERY> | school_finance | SELECT school_name FROM school ORDER BY enrollment LIMIT 1 | List the name of the school with the smallest enrollment. | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the average, maximum, minimum enrollment of all schools.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(enrollment) , max(enrollment) , min(enrollment) FROM school</SQL_QUERY> | school_finance | SELECT avg(enrollment) , max(enrollment) , min(enrollment) FROM school | Show the average, maximum, minimum enrollment of all schools. | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show each county along with the number of schools and total enrollment in each county.</question>
[SQL]:
| <SQL_QUERY>SELECT county , count(*) , sum(enrollment) FROM school GROUP BY county</SQL_QUERY> | school_finance | SELECT county , count(*) , sum(enrollment) FROM school GROUP BY county | Show each county along with the number of schools and total enrollment in each county. | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many donors have endowment for school named "Glenn"?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT T1.donator_name) FROM endowment AS T1 JOIN school AS T2 ON T1.school_id = T2.school_id WHERE T2.school_name = "Glenn"</SQL_QUERY> | school_finance | SELECT count(DISTINCT T1.donator_name) FROM endowment AS T1 JOIN school AS T2 ON T1.school_id = T2.school_id WHERE T2.school_name = "Glenn" | How many donors have endowment for school named "Glenn"? | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List each donator name and the amount of endowment in descending order of the amount of endowment.</question>
[SQL]:
| <SQL_QUERY>SELECT donator_name , sum(amount) FROM endowment GROUP BY donator_name ORDER BY sum(amount) DESC</SQL_QUERY> | school_finance | SELECT donator_name , sum(amount) FROM endowment GROUP BY donator_name ORDER BY sum(amount) DESC | List each donator name and the amount of endowment in descending order of the amount of endowment. | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of the schools without any endowment.</question>
[SQL]:
| <SQL_QUERY>SELECT school_name FROM school WHERE school_id NOT IN (SELECT school_id FROM endowment)</SQL_QUERY> | school_finance | SELECT school_name FROM school WHERE school_id NOT IN (SELECT school_id FROM endowment) | List the names of the schools without any endowment. | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List all the names of schools with an endowment amount smaller than or equal to 10.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.school_name FROM endowment AS T1 JOIN school AS T2 ON T1.school_id = T2.school_id GROUP BY T1.school_id HAVING sum(T1.amount) <= 10</SQL_QUERY> | school_finance | SELECT T2.school_name FROM endowment AS T1 JOIN school AS T2 ON T1.school_id = T2.school_id GROUP BY T1.school_id HAVING sum(T1.amount) <= 10 | List all the names of schools with an endowment amount smaller than or equal to 10. | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of donors who donated to both school "Glenn" and "Triton."</question>
[SQL]:
| <SQL_QUERY>SELECT T1.donator_name FROM endowment AS T1 JOIN school AS T2 ON T1.school_id = T2.school_id WHERE T2.school_name = 'Glenn' INTERSECT SELECT T1.donator_name FROM endowment AS T1 JOIN school AS T2 ON T1.school_id = T2.school_id WHERE T2.school_name = 'Triton'</SQL_QUERY> | school_finance | SELECT T1.donator_name FROM endowment AS T1 JOIN school AS T2 ON T1.school_id = T2.school_id WHERE T2.school_name = 'Glenn' INTERSECT SELECT T1.donator_name FROM endowment AS T1 JOIN school AS T2 ON T1.school_id = T2.school_id WHERE T2.school_name = 'Triton' | Show the names of donors who donated to both school "Glenn" and "Triton." | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of all the donors except those whose donation amount less than 9.</question>
[SQL]:
| <SQL_QUERY>SELECT donator_name FROM endowment EXCEPT SELECT donator_name FROM endowment WHERE amount < 9</SQL_QUERY> | school_finance | SELECT donator_name FROM endowment EXCEPT SELECT donator_name FROM endowment WHERE amount < 9 | Show the names of all the donors except those whose donation amount less than 9. | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text);</schema>"
<primary_keys>[Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id</primary_keys>"
<foreign_keys>[Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the amount and donor name for the largest amount of donation.</question>
[SQL]:
| <SQL_QUERY>SELECT amount , donator_name FROM endowment ORDER BY amount DESC LIMIT 1</SQL_QUERY> | school_finance | SELECT amount , donator_name FROM endowment ORDER BY amount DESC LIMIT 1 | List the amount and donor name for the largest amount of donation. | [Schema (values) (types)]: | school_finance | School : school_id (text) , school_name (text) , location (text) , mascot (text) , enrollment (text) , ihsaa_class (number) , ihsaa_football_class (text) , county (text) | budget : school_id (text) , year (text) , budgeted (text) , total_budget_percent_budgeted (text) , invested (text) , total_budget_percent_invested (number) , budget_invested_percent (text) | endowment : endowment_id (text) , school_id (text) , donator_name (text) , amount (text); | [Primary Keys]: school : school_id, budget : school_id, endowment : endowment_id | [Foreign Keys]: budget : school_id = school : school_id | endowment : school_id = school : school_id |
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