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)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text);</schema>"
<primary_keys>[Primary Keys]: staff : staff_id, customers : customer_id, products : product_id</primary_keys>"
<foreign_keys>[Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many customers are there in the customer type with the most customers?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM customers GROUP BY customer_type_code ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | customer_complaints | SELECT count(*) FROM customers GROUP BY customer_type_code ORDER BY count(*) DESC LIMIT 1 | How many customers are there in the customer type with the most customers? | [Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text); | [Primary Keys]: staff : staff_id, customers : customer_id, products : product_id | [Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text);</schema>"
<primary_keys>[Primary Keys]: staff : staff_id, customers : customer_id, products : product_id</primary_keys>"
<foreign_keys>[Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of customers that have the customer type that is most common.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM customers GROUP BY customer_type_code ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | customer_complaints | SELECT count(*) FROM customers GROUP BY customer_type_code ORDER BY count(*) DESC LIMIT 1 | Count the number of customers that have the customer type that is most common. | [Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text); | [Primary Keys]: staff : staff_id, customers : customer_id, products : product_id | [Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text);</schema>"
<primary_keys>[Primary Keys]: staff : staff_id, customers : customer_id, products : product_id</primary_keys>"
<foreign_keys>[Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the last name of the staff who has handled the first ever complaint?</question>
[SQL]:
| <SQL_QUERY>SELECT t1.last_name FROM staff AS t1 JOIN complaints AS t2 ON t1.staff_id = t2.staff_id ORDER BY t2.date_complaint_raised LIMIT 1</SQL_QUERY> | customer_complaints | SELECT t1.last_name FROM staff AS t1 JOIN complaints AS t2 ON t1.staff_id = t2.staff_id ORDER BY t2.date_complaint_raised LIMIT 1 | What is the last name of the staff who has handled the first ever complaint? | [Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text); | [Primary Keys]: staff : staff_id, customers : customer_id, products : product_id | [Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text);</schema>"
<primary_keys>[Primary Keys]: staff : staff_id, customers : customer_id, products : product_id</primary_keys>"
<foreign_keys>[Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the last name of the staff member who handled the complaint with the earliest date raised.</question>
[SQL]:
| <SQL_QUERY>SELECT t1.last_name FROM staff AS t1 JOIN complaints AS t2 ON t1.staff_id = t2.staff_id ORDER BY t2.date_complaint_raised LIMIT 1</SQL_QUERY> | customer_complaints | SELECT t1.last_name FROM staff AS t1 JOIN complaints AS t2 ON t1.staff_id = t2.staff_id ORDER BY t2.date_complaint_raised LIMIT 1 | Return the last name of the staff member who handled the complaint with the earliest date raised. | [Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text); | [Primary Keys]: staff : staff_id, customers : customer_id, products : product_id | [Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text);</schema>"
<primary_keys>[Primary Keys]: staff : staff_id, customers : customer_id, products : product_id</primary_keys>"
<foreign_keys>[Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many distinct complaint type codes are there in the database?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT complaint_type_code) FROM complaints</SQL_QUERY> | customer_complaints | SELECT count(DISTINCT complaint_type_code) FROM complaints | How many distinct complaint type codes are there in the database? | [Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text); | [Primary Keys]: staff : staff_id, customers : customer_id, products : product_id | [Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text);</schema>"
<primary_keys>[Primary Keys]: staff : staff_id, customers : customer_id, products : product_id</primary_keys>"
<foreign_keys>[Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of different complaint type codes.</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT complaint_type_code) FROM complaints</SQL_QUERY> | customer_complaints | SELECT count(DISTINCT complaint_type_code) FROM complaints | Count the number of different complaint type codes. | [Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text); | [Primary Keys]: staff : staff_id, customers : customer_id, products : product_id | [Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text);</schema>"
<primary_keys>[Primary Keys]: staff : staff_id, customers : customer_id, products : product_id</primary_keys>"
<foreign_keys>[Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the address line 1 and 2 of the customer with email "vbogisich@example.org".</question>
[SQL]:
| <SQL_QUERY>SELECT address_line_1 , address_line_2 FROM customers WHERE email_address = "vbogisich@example.org"</SQL_QUERY> | customer_complaints | SELECT address_line_1 , address_line_2 FROM customers WHERE email_address = "vbogisich@example.org" | Find the address line 1 and 2 of the customer with email "vbogisich@example.org". | [Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text); | [Primary Keys]: staff : staff_id, customers : customer_id, products : product_id | [Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text);</schema>"
<primary_keys>[Primary Keys]: staff : staff_id, customers : customer_id, products : product_id</primary_keys>"
<foreign_keys>[Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are lines 1 and 2 of the addressed of the customer with the email "vbogisich@example.org"?</question>
[SQL]:
| <SQL_QUERY>SELECT address_line_1 , address_line_2 FROM customers WHERE email_address = "vbogisich@example.org"</SQL_QUERY> | customer_complaints | SELECT address_line_1 , address_line_2 FROM customers WHERE email_address = "vbogisich@example.org" | What are lines 1 and 2 of the addressed of the customer with the email "vbogisich@example.org"? | [Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text); | [Primary Keys]: staff : staff_id, customers : customer_id, products : product_id | [Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text);</schema>"
<primary_keys>[Primary Keys]: staff : staff_id, customers : customer_id, products : product_id</primary_keys>"
<foreign_keys>[Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of complaints with Product Failure type for each complaint status.</question>
[SQL]:
| <SQL_QUERY>SELECT complaint_status_code , count(*) FROM complaints WHERE complaint_type_code = "Product Failure" GROUP BY complaint_status_code</SQL_QUERY> | customer_complaints | SELECT complaint_status_code , count(*) FROM complaints WHERE complaint_type_code = "Product Failure" GROUP BY complaint_status_code | Find the number of complaints with Product Failure type for each complaint status. | [Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text); | [Primary Keys]: staff : staff_id, customers : customer_id, products : product_id | [Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text);</schema>"
<primary_keys>[Primary Keys]: staff : staff_id, customers : customer_id, products : product_id</primary_keys>"
<foreign_keys>[Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Of complaints with the type code "Product Failure", how many had each different status code?</question>
[SQL]:
| <SQL_QUERY>SELECT complaint_status_code , count(*) FROM complaints WHERE complaint_type_code = "Product Failure" GROUP BY complaint_status_code</SQL_QUERY> | customer_complaints | SELECT complaint_status_code , count(*) FROM complaints WHERE complaint_type_code = "Product Failure" GROUP BY complaint_status_code | Of complaints with the type code "Product Failure", how many had each different status code? | [Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text); | [Primary Keys]: staff : staff_id, customers : customer_id, products : product_id | [Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text);</schema>"
<primary_keys>[Primary Keys]: staff : staff_id, customers : customer_id, products : product_id</primary_keys>"
<foreign_keys>[Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is first names of the top 5 staff who have handled the greatest number of complaints?</question>
[SQL]:
| <SQL_QUERY>SELECT t1.first_name FROM staff AS t1 JOIN complaints AS t2 ON t1.staff_id = t2.staff_id GROUP BY t2.staff_id ORDER BY count(*) LIMIT 5</SQL_QUERY> | customer_complaints | SELECT t1.first_name FROM staff AS t1 JOIN complaints AS t2 ON t1.staff_id = t2.staff_id GROUP BY t2.staff_id ORDER BY count(*) LIMIT 5 | What is first names of the top 5 staff who have handled the greatest number of complaints? | [Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text); | [Primary Keys]: staff : staff_id, customers : customer_id, products : product_id | [Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text);</schema>"
<primary_keys>[Primary Keys]: staff : staff_id, customers : customer_id, products : product_id</primary_keys>"
<foreign_keys>[Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the first names of the 5 staff members who have handled the most complaints.</question>
[SQL]:
| <SQL_QUERY>SELECT t1.first_name FROM staff AS t1 JOIN complaints AS t2 ON t1.staff_id = t2.staff_id GROUP BY t2.staff_id ORDER BY count(*) LIMIT 5</SQL_QUERY> | customer_complaints | SELECT t1.first_name FROM staff AS t1 JOIN complaints AS t2 ON t1.staff_id = t2.staff_id GROUP BY t2.staff_id ORDER BY count(*) LIMIT 5 | Return the first names of the 5 staff members who have handled the most complaints. | [Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text); | [Primary Keys]: staff : staff_id, customers : customer_id, products : product_id | [Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text);</schema>"
<primary_keys>[Primary Keys]: staff : staff_id, customers : customer_id, products : product_id</primary_keys>"
<foreign_keys>[Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which state has the most customers?</question>
[SQL]:
| <SQL_QUERY>SELECT state FROM customers GROUP BY state ORDER BY count(*) LIMIT 1</SQL_QUERY> | customer_complaints | SELECT state FROM customers GROUP BY state ORDER BY count(*) LIMIT 1 | Which state has the most customers? | [Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text); | [Primary Keys]: staff : staff_id, customers : customer_id, products : product_id | [Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text);</schema>"
<primary_keys>[Primary Keys]: staff : staff_id, customers : customer_id, products : product_id</primary_keys>"
<foreign_keys>[Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Give the state that has the most customers.</question>
[SQL]:
| <SQL_QUERY>SELECT state FROM customers GROUP BY state ORDER BY count(*) LIMIT 1</SQL_QUERY> | customer_complaints | SELECT state FROM customers GROUP BY state ORDER BY count(*) LIMIT 1 | Give the state that has the most customers. | [Schema (values) (types)]: | customer_complaints | Staff : staff_id (text) , gender (number) , first_name (text) , last_name (text) , email_address (text) , phone_number (text) | Customers : customer_id (text) , customer_type_code (number) , address_line_1 (text) , address_line_2 (text) , town_city (text) , state (text) , email_address (text) , phone_number (number) | Products : product_id (text) , parent_product_id (number) , product_category_code (text) , date_product_first_available (text) , date_product_discontinued (text) , product_name (text) , product_description (text) , product_price (number) | Complaints : complaint_id (text) , product_id (number) , customer_id (text) , complaint_outcome_code (text) , complaint_status_code (text) , complaint_type_code (text) , date_complaint_raised (text) , date_complaint_closed (number) , staff_id (text); | [Primary Keys]: staff : staff_id, customers : customer_id, products : product_id | [Foreign Keys]: complaints : customer_id = customers : customer_id | complaints : product_id = products : product_id | complaints : staff_id = staff : staff_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many submissions are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM submission</SQL_QUERY> | workshop_paper | SELECT count(*) FROM submission | How many submissions are there? | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of submissions.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM submission</SQL_QUERY> | workshop_paper | SELECT count(*) FROM submission | Count the number of submissions. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the authors of submissions in ascending order of scores.</question>
[SQL]:
| <SQL_QUERY>SELECT Author FROM submission ORDER BY Scores ASC</SQL_QUERY> | workshop_paper | SELECT Author FROM submission ORDER BY Scores ASC | List the authors of submissions in ascending order of scores. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the author for each submission and list them in ascending order of submission score.</question>
[SQL]:
| <SQL_QUERY>SELECT Author FROM submission ORDER BY Scores ASC</SQL_QUERY> | workshop_paper | SELECT Author FROM submission ORDER BY Scores ASC | Find the author for each submission and list them in ascending order of submission score. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the authors of submissions and their colleges?</question>
[SQL]:
| <SQL_QUERY>SELECT Author , College FROM submission</SQL_QUERY> | workshop_paper | SELECT Author , College FROM submission | What are the authors of submissions and their colleges? | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each submission, show the author and their affiliated college.</question>
[SQL]:
| <SQL_QUERY>SELECT Author , College FROM submission</SQL_QUERY> | workshop_paper | SELECT Author , College FROM submission | For each submission, show the author and their affiliated college. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of authors from college "Florida" or "Temple"</question>
[SQL]:
| <SQL_QUERY>SELECT Author FROM submission WHERE College = "Florida" OR College = "Temple"</SQL_QUERY> | workshop_paper | SELECT Author FROM submission WHERE College = "Florida" OR College = "Temple" | Show the names of authors from college "Florida" or "Temple" | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which authors with submissions are from college "Florida" or "Temple"?</question>
[SQL]:
| <SQL_QUERY>SELECT Author FROM submission WHERE College = "Florida" OR College = "Temple"</SQL_QUERY> | workshop_paper | SELECT Author FROM submission WHERE College = "Florida" OR College = "Temple" | Which authors with submissions are from college "Florida" or "Temple"? | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average score of submissions?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Scores) FROM submission</SQL_QUERY> | workshop_paper | SELECT avg(Scores) FROM submission | What is the average score of submissions? | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Compute the average score of submissions.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Scores) FROM submission</SQL_QUERY> | workshop_paper | SELECT avg(Scores) FROM submission | Compute the average score of submissions. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the author of the submission with the highest score?</question>
[SQL]:
| <SQL_QUERY>SELECT Author FROM submission ORDER BY Scores DESC LIMIT 1</SQL_QUERY> | workshop_paper | SELECT Author FROM submission ORDER BY Scores DESC LIMIT 1 | What is the author of the submission with the highest score? | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the author who achieved the highest score in a submission.</question>
[SQL]:
| <SQL_QUERY>SELECT Author FROM submission ORDER BY Scores DESC LIMIT 1</SQL_QUERY> | workshop_paper | SELECT Author FROM submission ORDER BY Scores DESC LIMIT 1 | Find the author who achieved the highest score in a submission. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show different colleges along with the number of authors of submission from each college.</question>
[SQL]:
| <SQL_QUERY>SELECT College , COUNT(*) FROM submission GROUP BY College</SQL_QUERY> | workshop_paper | SELECT College , COUNT(*) FROM submission GROUP BY College | Show different colleges along with the number of authors of submission from each college. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each college, return the college name and the count of authors with submissions from that college.</question>
[SQL]:
| <SQL_QUERY>SELECT College , COUNT(*) FROM submission GROUP BY College</SQL_QUERY> | workshop_paper | SELECT College , COUNT(*) FROM submission GROUP BY College | For each college, return the college name and the count of authors with submissions from that college. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the most common college of authors of submissions.</question>
[SQL]:
| <SQL_QUERY>SELECT College FROM submission GROUP BY College ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | workshop_paper | SELECT College FROM submission GROUP BY College ORDER BY COUNT(*) DESC LIMIT 1 | Show the most common college of authors of submissions. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which college has the most authors with submissions?</question>
[SQL]:
| <SQL_QUERY>SELECT College FROM submission GROUP BY College ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | workshop_paper | SELECT College FROM submission GROUP BY College ORDER BY COUNT(*) DESC LIMIT 1 | Which college has the most authors with submissions? | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the colleges that have both authors with submission score larger than 90 and authors with submission score smaller than 80.</question>
[SQL]:
| <SQL_QUERY>SELECT College FROM submission WHERE Scores > 90 INTERSECT SELECT College FROM submission WHERE Scores < 80</SQL_QUERY> | workshop_paper | SELECT College FROM submission WHERE Scores > 90 INTERSECT SELECT College FROM submission WHERE Scores < 80 | Show the colleges that have both authors with submission score larger than 90 and authors with submission score smaller than 80. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which colleges have both authors with submission score above 90 and authors with submission score below 80?</question>
[SQL]:
| <SQL_QUERY>SELECT College FROM submission WHERE Scores > 90 INTERSECT SELECT College FROM submission WHERE Scores < 80</SQL_QUERY> | workshop_paper | SELECT College FROM submission WHERE Scores > 90 INTERSECT SELECT College FROM submission WHERE Scores < 80 | Which colleges have both authors with submission score above 90 and authors with submission score below 80? | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the authors of submissions and the acceptance results of their submissions.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Author , T1.Result FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID</SQL_QUERY> | workshop_paper | SELECT T2.Author , T1.Result FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID | Show the authors of submissions and the acceptance results of their submissions. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each submission, find its author and acceptance result.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Author , T1.Result FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID</SQL_QUERY> | workshop_paper | SELECT T2.Author , T1.Result FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID | For each submission, find its author and acceptance result. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the result of the submission with the highest score.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Result FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID ORDER BY T2.Scores DESC LIMIT 1</SQL_QUERY> | workshop_paper | SELECT T1.Result FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID ORDER BY T2.Scores DESC LIMIT 1 | Show the result of the submission with the highest score. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which submission received the highest score in acceptance result. Show me the result.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Result FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID ORDER BY T2.Scores DESC LIMIT 1</SQL_QUERY> | workshop_paper | SELECT T1.Result FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID ORDER BY T2.Scores DESC LIMIT 1 | Which submission received the highest score in acceptance result. Show me the result. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show each author and the number of workshops they submitted to.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Author , COUNT(DISTINCT T1.workshop_id) FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID GROUP BY T2.Author</SQL_QUERY> | workshop_paper | SELECT T2.Author , COUNT(DISTINCT T1.workshop_id) FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID GROUP BY T2.Author | Show each author and the number of workshops they submitted to. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many workshops did each author submit to? Return the author name and the number of workshops.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Author , COUNT(DISTINCT T1.workshop_id) FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID GROUP BY T2.Author</SQL_QUERY> | workshop_paper | SELECT T2.Author , COUNT(DISTINCT T1.workshop_id) FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID GROUP BY T2.Author | How many workshops did each author submit to? Return the author name and the number of workshops. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the authors who have submissions to more than one workshop.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Author FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID GROUP BY T2.Author HAVING COUNT(DISTINCT T1.workshop_id) > 1</SQL_QUERY> | workshop_paper | SELECT T2.Author FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID GROUP BY T2.Author HAVING COUNT(DISTINCT T1.workshop_id) > 1 | Show the authors who have submissions to more than one workshop. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which authors have submitted to more than one workshop?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Author FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID GROUP BY T2.Author HAVING COUNT(DISTINCT T1.workshop_id) > 1</SQL_QUERY> | workshop_paper | SELECT T2.Author FROM acceptance AS T1 JOIN submission AS T2 ON T1.Submission_ID = T2.Submission_ID GROUP BY T2.Author HAVING COUNT(DISTINCT T1.workshop_id) > 1 | Which authors have submitted to more than one workshop? | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the date and venue of each workshop in ascending alphabetical order of the venue.</question>
[SQL]:
| <SQL_QUERY>SELECT Date , Venue FROM workshop ORDER BY Venue</SQL_QUERY> | workshop_paper | SELECT Date , Venue FROM workshop ORDER BY Venue | Show the date and venue of each workshop in ascending alphabetical order of the venue. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Sort the each workshop in alphabetical order of the venue. Return the date and venue of each workshop.</question>
[SQL]:
| <SQL_QUERY>SELECT Date , Venue FROM workshop ORDER BY Venue</SQL_QUERY> | workshop_paper | SELECT Date , Venue FROM workshop ORDER BY Venue | Sort the each workshop in alphabetical order of the venue. Return the date and venue of each workshop. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the authors who do not have submission to any workshop.</question>
[SQL]:
| <SQL_QUERY>SELECT Author FROM submission WHERE Submission_ID NOT IN (SELECT Submission_ID FROM acceptance)</SQL_QUERY> | workshop_paper | SELECT Author FROM submission WHERE Submission_ID NOT IN (SELECT Submission_ID FROM acceptance) | List the authors who do not have submission to any workshop. | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id</primary_keys>"
<foreign_keys>[Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which authors did not submit to any workshop?</question>
[SQL]:
| <SQL_QUERY>SELECT Author FROM submission WHERE Submission_ID NOT IN (SELECT Submission_ID FROM acceptance)</SQL_QUERY> | workshop_paper | SELECT Author FROM submission WHERE Submission_ID NOT IN (SELECT Submission_ID FROM acceptance) | Which authors did not submit to any workshop? | [Schema (values) (types)]: | workshop_paper | workshop : workshop_id (text) , date (number) , venue (text) , name (text) | submission : submission_id (text) , scores (number) , author (text) , college (text) | Acceptance : submission_id (text) , workshop_id (number) , result (text); | [Primary Keys]: workshop : workshop_id, submission : submission_id, acceptance : submission_id | [Foreign Keys]: acceptance : workshop_id = workshop : workshop_id | acceptance : submission_id = submission : submission_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of investors in total.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM INVESTORS</SQL_QUERY> | tracking_share_transactions | SELECT count(*) FROM INVESTORS | Find the number of investors in total. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all investor details.</question>
[SQL]:
| <SQL_QUERY>SELECT Investor_details FROM INVESTORS</SQL_QUERY> | tracking_share_transactions | SELECT Investor_details FROM INVESTORS | Show all investor details. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all distinct lot details.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT lot_details FROM LOTS</SQL_QUERY> | tracking_share_transactions | SELECT DISTINCT lot_details FROM LOTS | Show all distinct lot details. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the maximum amount of transaction.</question>
[SQL]:
| <SQL_QUERY>SELECT max(amount_of_transaction) FROM TRANSACTIONS</SQL_QUERY> | tracking_share_transactions | SELECT max(amount_of_transaction) FROM TRANSACTIONS | Show the maximum amount of transaction. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all date and share count of transactions.</question>
[SQL]:
| <SQL_QUERY>SELECT date_of_transaction , share_count FROM TRANSACTIONS</SQL_QUERY> | tracking_share_transactions | SELECT date_of_transaction , share_count FROM TRANSACTIONS | Show all date and share count of transactions. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the total share of transactions?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(share_count) FROM TRANSACTIONS</SQL_QUERY> | tracking_share_transactions | SELECT sum(share_count) FROM TRANSACTIONS | What is the total share of transactions? | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all transaction ids with transaction code 'PUR'.</question>
[SQL]:
| <SQL_QUERY>SELECT transaction_id FROM TRANSACTIONS WHERE transaction_type_code = 'PUR'</SQL_QUERY> | tracking_share_transactions | SELECT transaction_id FROM TRANSACTIONS WHERE transaction_type_code = 'PUR' | Show all transaction ids with transaction code 'PUR'. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all dates of transactions whose type code is "SALE".</question>
[SQL]:
| <SQL_QUERY>SELECT date_of_transaction FROM TRANSACTIONS WHERE transaction_type_code = "SALE"</SQL_QUERY> | tracking_share_transactions | SELECT date_of_transaction FROM TRANSACTIONS WHERE transaction_type_code = "SALE" | Show all dates of transactions whose type code is "SALE". | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the average amount of transactions with type code "SALE".</question>
[SQL]:
| <SQL_QUERY>SELECT avg(amount_of_transaction) FROM TRANSACTIONS WHERE transaction_type_code = "SALE"</SQL_QUERY> | tracking_share_transactions | SELECT avg(amount_of_transaction) FROM TRANSACTIONS WHERE transaction_type_code = "SALE" | Show the average amount of transactions with type code "SALE". | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the description of transaction type with code "PUR".</question>
[SQL]:
| <SQL_QUERY>SELECT transaction_type_description FROM Ref_Transaction_Types WHERE transaction_type_code = "PUR"</SQL_QUERY> | tracking_share_transactions | SELECT transaction_type_description FROM Ref_Transaction_Types WHERE transaction_type_code = "PUR" | Show the description of transaction type with code "PUR". | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the minimum amount of transactions whose type code is "PUR" and whose share count is bigger than 50.</question>
[SQL]:
| <SQL_QUERY>SELECT min(amount_of_transaction) FROM TRANSACTIONS WHERE transaction_type_code = "PUR" AND share_count > 50</SQL_QUERY> | tracking_share_transactions | SELECT min(amount_of_transaction) FROM TRANSACTIONS WHERE transaction_type_code = "PUR" AND share_count > 50 | Show the minimum amount of transactions whose type code is "PUR" and whose share count is bigger than 50. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the maximum share count of transactions where the amount is smaller than 10000</question>
[SQL]:
| <SQL_QUERY>SELECT max(share_count) FROM TRANSACTIONS WHERE amount_of_transaction < 10000</SQL_QUERY> | tracking_share_transactions | SELECT max(share_count) FROM TRANSACTIONS WHERE amount_of_transaction < 10000 | Show the maximum share count of transactions where the amount is smaller than 10000 | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the dates of transactions if the share count is bigger than 100 or the amount is bigger than 1000.</question>
[SQL]:
| <SQL_QUERY>SELECT date_of_transaction FROM TRANSACTIONS WHERE share_count > 100 OR amount_of_transaction > 1000</SQL_QUERY> | tracking_share_transactions | SELECT date_of_transaction FROM TRANSACTIONS WHERE share_count > 100 OR amount_of_transaction > 1000 | Show the dates of transactions if the share count is bigger than 100 or the amount is bigger than 1000. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the transaction type descriptions and dates if the share count is smaller than 10.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.transaction_type_description , T2.date_of_transaction FROM Ref_Transaction_Types AS T1 JOIN TRANSACTIONS AS T2 ON T1.transaction_type_code = T2.transaction_type_code WHERE T2.share_count < 10</SQL_QUERY> | tracking_share_transactions | SELECT T1.transaction_type_description , T2.date_of_transaction FROM Ref_Transaction_Types AS T1 JOIN TRANSACTIONS AS T2 ON T1.transaction_type_code = T2.transaction_type_code WHERE T2.share_count < 10 | Show the transaction type descriptions and dates if the share count is smaller than 10. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show details of all investors if they make any transaction with share count greater than 100.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Investor_details FROM INVESTORS AS T1 JOIN TRANSACTIONS AS T2 ON T1.investor_id = T2.investor_id WHERE T2.share_count > 100</SQL_QUERY> | tracking_share_transactions | SELECT T1.Investor_details FROM INVESTORS AS T1 JOIN TRANSACTIONS AS T2 ON T1.investor_id = T2.investor_id WHERE T2.share_count > 100 | Show details of all investors if they make any transaction with share count greater than 100. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many distinct transaction types are used in the transactions?</question>
[SQL]:
| <SQL_QUERY>SELECT COUNT(DISTINCT transaction_type_code) FROM TRANSACTIONS</SQL_QUERY> | tracking_share_transactions | SELECT COUNT(DISTINCT transaction_type_code) FROM TRANSACTIONS | How many distinct transaction types are used in the transactions? | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the lot details and investor ids.</question>
[SQL]:
| <SQL_QUERY>SELECT lot_details , investor_id FROM LOTS</SQL_QUERY> | tracking_share_transactions | SELECT lot_details , investor_id FROM LOTS | Return the lot details and investor ids. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the lot details of lots that belong to investors with details "l"?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.lot_details FROM INVESTORS AS T1 JOIN LOTS AS T2 ON T1.investor_id = T2.investor_id WHERE T1.Investor_details = "l"</SQL_QUERY> | tracking_share_transactions | SELECT T2.lot_details FROM INVESTORS AS T1 JOIN LOTS AS T2 ON T1.investor_id = T2.investor_id WHERE T1.Investor_details = "l" | Return the lot details of lots that belong to investors with details "l"? | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the purchase details of transactions with amount bigger than 10000?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.purchase_details FROM PURCHASES AS T1 JOIN TRANSACTIONS AS T2 ON T1.purchase_transaction_id = T2.transaction_id WHERE T2.amount_of_transaction > 10000</SQL_QUERY> | tracking_share_transactions | SELECT T1.purchase_details FROM PURCHASES AS T1 JOIN TRANSACTIONS AS T2 ON T1.purchase_transaction_id = T2.transaction_id WHERE T2.amount_of_transaction > 10000 | What are the purchase details of transactions with amount bigger than 10000? | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the sale details and dates of transactions with amount smaller than 3000?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.sales_details , T2.date_of_transaction FROM SALES AS T1 JOIN TRANSACTIONS AS T2 ON T1.sales_transaction_id = T2.transaction_id WHERE T2.amount_of_transaction < 3000</SQL_QUERY> | tracking_share_transactions | SELECT T1.sales_details , T2.date_of_transaction FROM SALES AS T1 JOIN TRANSACTIONS AS T2 ON T1.sales_transaction_id = T2.transaction_id WHERE T2.amount_of_transaction < 3000 | What are the sale details and dates of transactions with amount smaller than 3000? | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the lot details of lots associated with transactions with share count smaller than 50?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.lot_details FROM LOTS AS T1 JOIN TRANSACTIONS_LOTS AS T2 ON T1.lot_id = T2.transaction_id JOIN TRANSACTIONS AS T3 ON T2.transaction_id = T3.transaction_id WHERE T3.share_count < 50</SQL_QUERY> | tracking_share_transactions | SELECT T1.lot_details FROM LOTS AS T1 JOIN TRANSACTIONS_LOTS AS T2 ON T1.lot_id = T2.transaction_id JOIN TRANSACTIONS AS T3 ON T2.transaction_id = T3.transaction_id WHERE T3.share_count < 50 | What are the lot details of lots associated with transactions with share count smaller than 50? | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the lot details of lots associated with transactions whose share count is bigger than 100 and whose type code is "PUR"?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.lot_details FROM LOTS AS T1 JOIN TRANSACTIONS_LOTS AS T2 ON T1.lot_id = T2.transaction_id JOIN TRANSACTIONS AS T3 ON T2.transaction_id = T3.transaction_id WHERE T3.share_count > 100 AND T3.transaction_type_code = "PUR"</SQL_QUERY> | tracking_share_transactions | SELECT T1.lot_details FROM LOTS AS T1 JOIN TRANSACTIONS_LOTS AS T2 ON T1.lot_id = T2.transaction_id JOIN TRANSACTIONS AS T3 ON T2.transaction_id = T3.transaction_id WHERE T3.share_count > 100 AND T3.transaction_type_code = "PUR" | What are the lot details of lots associated with transactions whose share count is bigger than 100 and whose type code is "PUR"? | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the average transaction amount for different transaction types.</question>
[SQL]:
| <SQL_QUERY>SELECT transaction_type_code , avg(amount_of_transaction) FROM TRANSACTIONS GROUP BY transaction_type_code</SQL_QUERY> | tracking_share_transactions | SELECT transaction_type_code , avg(amount_of_transaction) FROM TRANSACTIONS GROUP BY transaction_type_code | Show the average transaction amount for different transaction types. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the maximum and minimum share count of different transaction types.</question>
[SQL]:
| <SQL_QUERY>SELECT transaction_type_code , max(share_count) , min(share_count) FROM TRANSACTIONS GROUP BY transaction_type_code</SQL_QUERY> | tracking_share_transactions | SELECT transaction_type_code , max(share_count) , min(share_count) FROM TRANSACTIONS GROUP BY transaction_type_code | Show the maximum and minimum share count of different transaction types. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the average share count of transactions for different investors.</question>
[SQL]:
| <SQL_QUERY>SELECT investor_id , avg(share_count) FROM TRANSACTIONS GROUP BY investor_id</SQL_QUERY> | tracking_share_transactions | SELECT investor_id , avg(share_count) FROM TRANSACTIONS GROUP BY investor_id | Show the average share count of transactions for different investors. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the average share count of transactions each each investor, ordered by average share count.</question>
[SQL]:
| <SQL_QUERY>SELECT investor_id , avg(share_count) FROM TRANSACTIONS GROUP BY investor_id ORDER BY avg(share_count)</SQL_QUERY> | tracking_share_transactions | SELECT investor_id , avg(share_count) FROM TRANSACTIONS GROUP BY investor_id ORDER BY avg(share_count) | Show the average share count of transactions each each investor, ordered by average share count. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the average amount of transactions for different investors.</question>
[SQL]:
| <SQL_QUERY>SELECT investor_id , avg(amount_of_transaction) FROM TRANSACTIONS GROUP BY investor_id</SQL_QUERY> | tracking_share_transactions | SELECT investor_id , avg(amount_of_transaction) FROM TRANSACTIONS GROUP BY investor_id | Show the average amount of transactions for different investors. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the average amount of transactions for different lots.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.lot_id , avg(amount_of_transaction) FROM TRANSACTIONS AS T1 JOIN Transactions_Lots AS T2 ON T1.transaction_id = T2.transaction_id GROUP BY T2.lot_id</SQL_QUERY> | tracking_share_transactions | SELECT T2.lot_id , avg(amount_of_transaction) FROM TRANSACTIONS AS T1 JOIN Transactions_Lots AS T2 ON T1.transaction_id = T2.transaction_id GROUP BY T2.lot_id | Show the average amount of transactions for different lots. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the average amount of transactions for different lots, ordered by average amount of transactions.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.lot_id , avg(amount_of_transaction) FROM TRANSACTIONS AS T1 JOIN Transactions_Lots AS T2 ON T1.transaction_id = T2.transaction_id GROUP BY T2.lot_id ORDER BY avg(amount_of_transaction)</SQL_QUERY> | tracking_share_transactions | SELECT T2.lot_id , avg(amount_of_transaction) FROM TRANSACTIONS AS T1 JOIN Transactions_Lots AS T2 ON T1.transaction_id = T2.transaction_id GROUP BY T2.lot_id ORDER BY avg(amount_of_transaction) | Show the average amount of transactions for different lots, ordered by average amount of transactions. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the number of transactions with transaction type code "SALE" for different investors if it is larger than 0.</question>
[SQL]:
| <SQL_QUERY>SELECT investor_id , COUNT(*) FROM TRANSACTIONS WHERE transaction_type_code = "SALE" GROUP BY investor_id</SQL_QUERY> | tracking_share_transactions | SELECT investor_id , COUNT(*) FROM TRANSACTIONS WHERE transaction_type_code = "SALE" GROUP BY investor_id | Show the number of transactions with transaction type code "SALE" for different investors if it is larger than 0. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the number of transactions for different investors.</question>
[SQL]:
| <SQL_QUERY>SELECT investor_id , COUNT(*) FROM TRANSACTIONS GROUP BY investor_id</SQL_QUERY> | tracking_share_transactions | SELECT investor_id , COUNT(*) FROM TRANSACTIONS GROUP BY investor_id | Show the number of transactions for different investors. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the transaction type code that occurs the fewest times.</question>
[SQL]:
| <SQL_QUERY>SELECT transaction_type_code FROM TRANSACTIONS GROUP BY transaction_type_code ORDER BY COUNT(*) ASC LIMIT 1</SQL_QUERY> | tracking_share_transactions | SELECT transaction_type_code FROM TRANSACTIONS GROUP BY transaction_type_code ORDER BY COUNT(*) ASC LIMIT 1 | Show the transaction type code that occurs the fewest times. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the transaction type code that occurs the most frequently.</question>
[SQL]:
| <SQL_QUERY>SELECT transaction_type_code FROM TRANSACTIONS GROUP BY transaction_type_code ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | tracking_share_transactions | SELECT transaction_type_code FROM TRANSACTIONS GROUP BY transaction_type_code ORDER BY COUNT(*) DESC LIMIT 1 | Show the transaction type code that occurs the most frequently. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the description of the transaction type that occurs most frequently.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.transaction_type_description FROM Ref_Transaction_Types AS T1 JOIN TRANSACTIONS AS T2 ON T1.transaction_type_code = T2.transaction_type_code GROUP BY T1.transaction_type_code ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | tracking_share_transactions | SELECT T1.transaction_type_description FROM Ref_Transaction_Types AS T1 JOIN TRANSACTIONS AS T2 ON T1.transaction_type_code = T2.transaction_type_code GROUP BY T1.transaction_type_code ORDER BY COUNT(*) DESC LIMIT 1 | Show the description of the transaction type that occurs most frequently. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the id and details of the investor that has the largest number of transactions.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.investor_id , T1.Investor_details FROM INVESTORS AS T1 JOIN TRANSACTIONS AS T2 ON T1.investor_id = T2.investor_id GROUP BY T2.investor_id ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | tracking_share_transactions | SELECT T2.investor_id , T1.Investor_details FROM INVESTORS AS T1 JOIN TRANSACTIONS AS T2 ON T1.investor_id = T2.investor_id GROUP BY T2.investor_id ORDER BY COUNT(*) DESC LIMIT 1 | Show the id and details of the investor that has the largest number of transactions. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the id and details for the investors who have the top 3 number of transactions.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.investor_id , T1.Investor_details FROM INVESTORS AS T1 JOIN TRANSACTIONS AS T2 ON T1.investor_id = T2.investor_id GROUP BY T2.investor_id ORDER BY COUNT(*) DESC LIMIT 3</SQL_QUERY> | tracking_share_transactions | SELECT T2.investor_id , T1.Investor_details FROM INVESTORS AS T1 JOIN TRANSACTIONS AS T2 ON T1.investor_id = T2.investor_id GROUP BY T2.investor_id ORDER BY COUNT(*) DESC LIMIT 3 | Show the id and details for the investors who have the top 3 number of transactions. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the ids of the investors who have at least two transactions.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.investor_id FROM INVESTORS AS T1 JOIN TRANSACTIONS AS T2 ON T1.investor_id = T2.investor_id GROUP BY T2.investor_id HAVING COUNT(*) >= 2</SQL_QUERY> | tracking_share_transactions | SELECT T2.investor_id FROM INVESTORS AS T1 JOIN TRANSACTIONS AS T2 ON T1.investor_id = T2.investor_id GROUP BY T2.investor_id HAVING COUNT(*) >= 2 | Show the ids of the investors who have at least two transactions. | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the ids and details of the investors who have at least two transactions with type code "SALE".</question>
[SQL]:
| <SQL_QUERY>SELECT T2.investor_id , T1.Investor_details FROM INVESTORS AS T1 JOIN TRANSACTIONS AS T2 ON T1.investor_id = T2.investor_id WHERE T2.transaction_type_code = "SALE" GROUP BY T2.investor_id HAVING COUNT(*) >= 2</SQL_QUERY> | tracking_share_transactions | SELECT T2.investor_id , T1.Investor_details FROM INVESTORS AS T1 JOIN TRANSACTIONS AS T2 ON T1.investor_id = T2.investor_id WHERE T2.transaction_type_code = "SALE" GROUP BY T2.investor_id HAVING COUNT(*) >= 2 | Show the ids and details of the investors who have at least two transactions with type code "SALE". | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the dates of transactions with at least 100 share count or amount bigger than 100?</question>
[SQL]:
| <SQL_QUERY>SELECT date_of_transaction FROM TRANSACTIONS WHERE share_count >= 100 OR amount_of_transaction >= 100</SQL_QUERY> | tracking_share_transactions | SELECT date_of_transaction FROM TRANSACTIONS WHERE share_count >= 100 OR amount_of_transaction >= 100 | What are the dates of transactions with at least 100 share count or amount bigger than 100? | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the details of all sales and purchases?</question>
[SQL]:
| <SQL_QUERY>SELECT sales_details FROM sales UNION SELECT purchase_details FROM purchases</SQL_QUERY> | tracking_share_transactions | SELECT sales_details FROM sales UNION SELECT purchase_details FROM purchases | What are the details of all sales and purchases? | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number);</schema>"
<primary_keys>[Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the details of the lots which are not used in any transactions?</question>
[SQL]:
| <SQL_QUERY>SELECT lot_details FROM Lots EXCEPT SELECT T1.lot_details FROM Lots AS T1 JOIN transactions_lots AS T2 ON T1.lot_id = T2.lot_id</SQL_QUERY> | tracking_share_transactions | SELECT lot_details FROM Lots EXCEPT SELECT T1.lot_details FROM Lots AS T1 JOIN transactions_lots AS T2 ON T1.lot_id = T2.lot_id | What are the details of the lots which are not used in any transactions? | [Schema (values) (types)]: | tracking_share_transactions | Investors : investor_id (text) , investor_details (number) | Lots : lot_id (text) , investor_id (number) , lot_details (text) | Ref_Transaction_Types : transaction_type_code (text) , transaction_type_description (number) | Transactions : transaction_id (text) , investor_id (number) , transaction_type_code (text) , date_of_transaction (number) , amount_of_transaction (number) , share_count (text) , other_details (text) | Sales : sales_transaction_id (text) , sales_details (number) | Purchases : purchase_transaction_id (text) , purchase_details (number) | Transactions_Lots : transaction_id (text) , lot_id (number); | [Primary Keys]: investors : investor_id, lots : lot_id, ref_transaction_types : transaction_type_code, transactions : transaction_id, sales : sales_transaction_id | [Foreign Keys]: lots : investor_id = investors : investor_id | transactions : transaction_type_code = ref_transaction_types : transaction_type_code | transactions : investor_id = investors : investor_id | sales : sales_transaction_id = transactions : transaction_id | purchases : purchase_transaction_id = transactions : transaction_id | transactions_lots : transaction_id = transactions : transaction_id | transactions_lots : lot_id = lots : lot_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many available hotels are there in total?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM HOTELS</SQL_QUERY> | cre_Theme_park | SELECT count(*) FROM HOTELS | How many available hotels are there in total? | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the total number of available hotels.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM HOTELS</SQL_QUERY> | cre_Theme_park | SELECT count(*) FROM HOTELS | Find the total number of available hotels. | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the price ranges of hotels?</question>
[SQL]:
| <SQL_QUERY>SELECT price_range FROM HOTELS</SQL_QUERY> | cre_Theme_park | SELECT price_range FROM HOTELS | What are the price ranges of hotels? | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Tell me the price ranges for all the hotels.</question>
[SQL]:
| <SQL_QUERY>SELECT price_range FROM HOTELS</SQL_QUERY> | cre_Theme_park | SELECT price_range FROM HOTELS | Tell me the price ranges for all the hotels. | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all distinct location names.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT Location_Name FROM LOCATIONS</SQL_QUERY> | cre_Theme_park | SELECT DISTINCT Location_Name FROM LOCATIONS | Show all distinct location names. | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct location names?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT Location_Name FROM LOCATIONS</SQL_QUERY> | cre_Theme_park | SELECT DISTINCT Location_Name FROM LOCATIONS | What are the distinct location names? | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names and details of all the staff members.</question>
[SQL]:
| <SQL_QUERY>SELECT Name , Other_Details FROM Staff</SQL_QUERY> | cre_Theme_park | SELECT Name , Other_Details FROM Staff | Show the names and details of all the staff members. | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name and detail of each staff member?</question>
[SQL]:
| <SQL_QUERY>SELECT Name , Other_Details FROM Staff</SQL_QUERY> | cre_Theme_park | SELECT Name , Other_Details FROM Staff | What is the name and detail of each staff member? | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show details of all visitors.</question>
[SQL]:
| <SQL_QUERY>SELECT Tourist_Details FROM VISITORS</SQL_QUERY> | cre_Theme_park | SELECT Tourist_Details FROM VISITORS | Show details of all visitors. | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the detail of each visitor?</question>
[SQL]:
| <SQL_QUERY>SELECT Tourist_Details FROM VISITORS</SQL_QUERY> | cre_Theme_park | SELECT Tourist_Details FROM VISITORS | What is the detail of each visitor? | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the price ranges of hotels with 5 star ratings.</question>
[SQL]:
| <SQL_QUERY>SELECT price_range FROM HOTELS WHERE star_rating_code = "5"</SQL_QUERY> | cre_Theme_park | SELECT price_range FROM HOTELS WHERE star_rating_code = "5" | Show the price ranges of hotels with 5 star ratings. | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the price ranges of five star hotels?</question>
[SQL]:
| <SQL_QUERY>SELECT price_range FROM HOTELS WHERE star_rating_code = "5"</SQL_QUERY> | cre_Theme_park | SELECT price_range FROM HOTELS WHERE star_rating_code = "5" | What are the price ranges of five star hotels? | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the average price range of hotels that have 5 star ratings and allow pets.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(price_range) FROM HOTELS WHERE star_rating_code = "5" AND pets_allowed_yn = 1</SQL_QUERY> | cre_Theme_park | SELECT avg(price_range) FROM HOTELS WHERE star_rating_code = "5" AND pets_allowed_yn = 1 | Show the average price range of hotels that have 5 star ratings and allow pets. | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average price range of five star hotels that allow pets?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(price_range) FROM HOTELS WHERE star_rating_code = "5" AND pets_allowed_yn = 1</SQL_QUERY> | cre_Theme_park | SELECT avg(price_range) FROM HOTELS WHERE star_rating_code = "5" AND pets_allowed_yn = 1 | What is the average price range of five star hotels that allow pets? | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_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)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text);</schema>"
<primary_keys>[Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id</primary_keys>"
<foreign_keys>[Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the address of the location "UK Gallery"?</question>
[SQL]:
| <SQL_QUERY>SELECT Address FROM LOCATIONS WHERE Location_Name = "UK Gallery"</SQL_QUERY> | cre_Theme_park | SELECT Address FROM LOCATIONS WHERE Location_Name = "UK Gallery" | What is the address of the location "UK Gallery"? | [Schema (values) (types)]: | cre_Theme_park | Ref_Hotel_Star_Ratings : star_rating_code (text) , star_rating_description (text) | Locations : location_id (text) , location_name (text) , address (text) , other_details (number) | Ref_Attraction_Types : attraction_type_code (text) , attraction_type_description (text) | Visitors : tourist_id (text) , tourist_details (text) | Features : feature_id (text) , feature_details (text) | Hotels : hotel_id (text) , star_rating_code (text) , pets_allowed_yn (text) , price_range (number) , other_hotel_details (text) | Tourist_Attractions : tourist_attraction_id (text) , attraction_type_code (text) , location_id (text) , how_to_get_there (number) , name (text) , description (text) , opening_hours (text) , other_details (text) | Street_Markets : market_id (text) , market_details (text) | Shops : shop_id (text) , shop_details (text) | Museums : museum_id (text) , museum_details (text) | Royal_Family : royal_family_id (text) , royal_family_details (text) | Theme_Parks : theme_park_id (text) , theme_park_details (text) | Visits : visit_id (text) , tourist_attraction_id (text) , tourist_id (text) , visit_date (number) , visit_details (text) | Photos : photo_id (text) , tourist_attraction_id (text) , name (text) , description (number) , filename (text) , other_details (text) | Staff : staff_id (text) , tourist_attraction_id (text) , name (text) , other_details (number) | Tourist_Attraction_Features : tourist_attraction_id (text) , feature_id (text); | [Primary Keys]: ref_hotel_star_ratings : star_rating_code, locations : location_id, ref_attraction_types : attraction_type_code, visitors : tourist_id, features : feature_id, hotels : hotel_id, tourist_attractions : tourist_attraction_id, street_markets : market_id, shops : shop_id, museums : museum_id, royal_family : royal_family_id, theme_parks : theme_park_id, visits : visit_id, photos : photo_id, staff : staff_id, tourist_attraction_features : tourist_attraction_id | [Foreign Keys]: hotels : star_rating_code = ref_hotel_star_ratings : star_rating_code | tourist_attractions : attraction_type_code = ref_attraction_types : attraction_type_code | tourist_attractions : location_id = locations : location_id | street_markets : market_id = tourist_attractions : tourist_attraction_id | shops : shop_id = tourist_attractions : tourist_attraction_id | museums : museum_id = tourist_attractions : tourist_attraction_id | royal_family : royal_family_id = tourist_attractions : tourist_attraction_id | theme_parks : theme_park_id = tourist_attractions : tourist_attraction_id | visits : tourist_id = visitors : tourist_id | visits : tourist_attraction_id = tourist_attractions : tourist_attraction_id | photos : tourist_attraction_id = tourist_attractions : tourist_attraction_id | staff : tourist_attraction_id = tourist_attractions : tourist_attraction_id | tourist_attraction_features : feature_id = features : feature_id | tourist_attraction_features : tourist_attraction_id = tourist_attractions : tourist_attraction_id |
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