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)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all the documents, as well as the access counts of each, ordered alphabetically?</question>
[SQL]:
| <SQL_QUERY>SELECT document_name , access_count FROM documents ORDER BY document_name</SQL_QUERY> | document_management | SELECT document_name , access_count FROM documents ORDER BY document_name | What are the names of all the documents, as well as the access counts of each, ordered alphabetically? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of the document that has been accessed the greatest number of times, as well as the count of how many times it has been accessed?</question>
[SQL]:
| <SQL_QUERY>SELECT document_name , access_count FROM documents ORDER BY access_count DESC LIMIT 1</SQL_QUERY> | document_management | SELECT document_name , access_count FROM documents ORDER BY access_count DESC LIMIT 1 | Find the name of the document that has been accessed the greatest number of times, as well as the count of how many times it has been accessed? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of the document which has been accessed the most times, as well as the number of times it has been accessed?</question>
[SQL]:
| <SQL_QUERY>SELECT document_name , access_count FROM documents ORDER BY access_count DESC LIMIT 1</SQL_QUERY> | document_management | SELECT document_name , access_count FROM documents ORDER BY access_count DESC LIMIT 1 | What is the name of the document which has been accessed the most times, as well as the number of times it has been accessed? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the types of documents with more than 4 documents.</question>
[SQL]:
| <SQL_QUERY>SELECT document_type_code FROM documents GROUP BY document_type_code HAVING count(*) > 4</SQL_QUERY> | document_management | SELECT document_type_code FROM documents GROUP BY document_type_code HAVING count(*) > 4 | Find the types of documents with more than 4 documents. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the codes of types of documents of which there are for or more?</question>
[SQL]:
| <SQL_QUERY>SELECT document_type_code FROM documents GROUP BY document_type_code HAVING count(*) > 4</SQL_QUERY> | document_management | SELECT document_type_code FROM documents GROUP BY document_type_code HAVING count(*) > 4 | What are the codes of types of documents of which there are for or more? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the total access count of all documents in the most popular document type.</question>
[SQL]:
| <SQL_QUERY>SELECT sum(access_count) FROM documents GROUP BY document_type_code ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | document_management | SELECT sum(access_count) FROM documents GROUP BY document_type_code ORDER BY count(*) DESC LIMIT 1 | Find the total access count of all documents in the most popular document type. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the total access count of documents that are of the most common document type?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(access_count) FROM documents GROUP BY document_type_code ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | document_management | SELECT sum(access_count) FROM documents GROUP BY document_type_code ORDER BY count(*) DESC LIMIT 1 | What is the total access count of documents that are of the most common document type? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average access count of documents?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(access_count) FROM documents</SQL_QUERY> | document_management | SELECT avg(access_count) FROM documents | What is the average access count of documents? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the average access count across all documents?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(access_count) FROM documents</SQL_QUERY> | document_management | SELECT avg(access_count) FROM documents | Find the average access count across all documents? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the structure of the document with the least number of accesses?</question>
[SQL]:
| <SQL_QUERY>SELECT t2.document_structure_description FROM documents AS t1 JOIN document_structures AS t2 ON t1.document_structure_code = t2.document_structure_code GROUP BY t1.document_structure_code ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | document_management | SELECT t2.document_structure_description FROM documents AS t1 JOIN document_structures AS t2 ON t1.document_structure_code = t2.document_structure_code GROUP BY t1.document_structure_code ORDER BY count(*) DESC LIMIT 1 | What is the structure of the document with the least number of accesses? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the structure description of the document that has been accessed the fewest number of times.</question>
[SQL]:
| <SQL_QUERY>SELECT t2.document_structure_description FROM documents AS t1 JOIN document_structures AS t2 ON t1.document_structure_code = t2.document_structure_code GROUP BY t1.document_structure_code ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | document_management | SELECT t2.document_structure_description FROM documents AS t1 JOIN document_structures AS t2 ON t1.document_structure_code = t2.document_structure_code GROUP BY t1.document_structure_code ORDER BY count(*) DESC LIMIT 1 | Return the structure description of the document that has been accessed the fewest number of times. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the type of the document named "David CV"?</question>
[SQL]:
| <SQL_QUERY>SELECT document_type_code FROM documents WHERE document_name = "David CV"</SQL_QUERY> | document_management | SELECT document_type_code FROM documents WHERE document_name = "David CV" | What is the type of the document named "David CV"? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the type code of the document named "David CV".</question>
[SQL]:
| <SQL_QUERY>SELECT document_type_code FROM documents WHERE document_name = "David CV"</SQL_QUERY> | document_management | SELECT document_type_code FROM documents WHERE document_name = "David CV" | Return the type code of the document named "David CV". | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the list of documents that are both in the most three popular type and have the most three popular structure.</question>
[SQL]:
| <SQL_QUERY>SELECT document_name FROM documents GROUP BY document_type_code ORDER BY count(*) DESC LIMIT 3 INTERSECT SELECT document_name FROM documents GROUP BY document_structure_code ORDER BY count(*) DESC LIMIT 3</SQL_QUERY> | document_management | SELECT document_name FROM documents GROUP BY document_type_code ORDER BY count(*) DESC LIMIT 3 INTERSECT SELECT document_name FROM documents GROUP BY document_structure_code ORDER BY count(*) DESC LIMIT 3 | Find the list of documents that are both in the most three popular type and have the most three popular structure. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of documents that have both one of the three most common types and one of three most common structures?</question>
[SQL]:
| <SQL_QUERY>SELECT document_name FROM documents GROUP BY document_type_code ORDER BY count(*) DESC LIMIT 3 INTERSECT SELECT document_name FROM documents GROUP BY document_structure_code ORDER BY count(*) DESC LIMIT 3</SQL_QUERY> | document_management | SELECT document_name FROM documents GROUP BY document_type_code ORDER BY count(*) DESC LIMIT 3 INTERSECT SELECT document_name FROM documents GROUP BY document_structure_code ORDER BY count(*) DESC LIMIT 3 | What are the names of documents that have both one of the three most common types and one of three most common structures? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What document types do have more than 10000 total access number.</question>
[SQL]:
| <SQL_QUERY>SELECT document_type_code FROM documents GROUP BY document_type_code HAVING sum(access_count) > 10000</SQL_QUERY> | document_management | SELECT document_type_code FROM documents GROUP BY document_type_code HAVING sum(access_count) > 10000 | What document types do have more than 10000 total access number. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the codes of the document types that do not have a total access count of over 10000.</question>
[SQL]:
| <SQL_QUERY>SELECT document_type_code FROM documents GROUP BY document_type_code HAVING sum(access_count) > 10000</SQL_QUERY> | document_management | SELECT document_type_code FROM documents GROUP BY document_type_code HAVING sum(access_count) > 10000 | Return the codes of the document types that do not have a total access count of over 10000. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are all the section titles of the document named "David CV"?</question>
[SQL]:
| <SQL_QUERY>SELECT t2.section_title FROM documents AS t1 JOIN document_sections AS t2 ON t1.document_code = t2.document_code WHERE t1.document_name = "David CV"</SQL_QUERY> | document_management | SELECT t2.section_title FROM documents AS t1 JOIN document_sections AS t2 ON t1.document_code = t2.document_code WHERE t1.document_name = "David CV" | What are all the section titles of the document named "David CV"? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Give the section titles of the document with the name "David CV".</question>
[SQL]:
| <SQL_QUERY>SELECT t2.section_title FROM documents AS t1 JOIN document_sections AS t2 ON t1.document_code = t2.document_code WHERE t1.document_name = "David CV"</SQL_QUERY> | document_management | SELECT t2.section_title FROM documents AS t1 JOIN document_sections AS t2 ON t1.document_code = t2.document_code WHERE t1.document_name = "David CV" | Give the section titles of the document with the name "David CV". | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find all the name of documents without any sections.</question>
[SQL]:
| <SQL_QUERY>SELECT document_name FROM documents WHERE document_code NOT IN (SELECT document_code FROM document_sections)</SQL_QUERY> | document_management | SELECT document_name FROM documents WHERE document_code NOT IN (SELECT document_code FROM document_sections) | Find all the name of documents without any sections. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of documents that do not have any sections?</question>
[SQL]:
| <SQL_QUERY>SELECT document_name FROM documents WHERE document_code NOT IN (SELECT document_code FROM document_sections)</SQL_QUERY> | document_management | SELECT document_name FROM documents WHERE document_code NOT IN (SELECT document_code FROM document_sections) | What are the names of documents that do not have any sections? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List all the username and passwords of users with the most popular role.</question>
[SQL]:
| <SQL_QUERY>SELECT user_name , password FROM users GROUP BY role_code ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | document_management | SELECT user_name , password FROM users GROUP BY role_code ORDER BY count(*) DESC LIMIT 1 | List all the username and passwords of users with the most popular role. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the usernames and passwords of users that have the most common role?</question>
[SQL]:
| <SQL_QUERY>SELECT user_name , password FROM users GROUP BY role_code ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | document_management | SELECT user_name , password FROM users GROUP BY role_code ORDER BY count(*) DESC LIMIT 1 | What are the usernames and passwords of users that have the most common role? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the average access counts of documents with functional area "Acknowledgement".</question>
[SQL]:
| <SQL_QUERY>SELECT avg(t1.access_count) FROM documents AS t1 JOIN document_functional_areas AS t2 ON t1.document_code = t2.document_code JOIN functional_areas AS t3 ON t2.functional_area_code = t3.functional_area_code WHERE t3.functional_area_description = "Acknowledgement"</SQL_QUERY> | document_management | SELECT avg(t1.access_count) FROM documents AS t1 JOIN document_functional_areas AS t2 ON t1.document_code = t2.document_code JOIN functional_areas AS t3 ON t2.functional_area_code = t3.functional_area_code WHERE t3.functional_area_description = "Acknowledgement" | Find the average access counts of documents with functional area "Acknowledgement". | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the average access counts of documents that have the functional area description "Acknowledgement"?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(t1.access_count) FROM documents AS t1 JOIN document_functional_areas AS t2 ON t1.document_code = t2.document_code JOIN functional_areas AS t3 ON t2.functional_area_code = t3.functional_area_code WHERE t3.functional_area_description = "Acknowledgement"</SQL_QUERY> | document_management | SELECT avg(t1.access_count) FROM documents AS t1 JOIN document_functional_areas AS t2 ON t1.document_code = t2.document_code JOIN functional_areas AS t3 ON t2.functional_area_code = t3.functional_area_code WHERE t3.functional_area_description = "Acknowledgement" | What are the average access counts of documents that have the functional area description "Acknowledgement"? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find names of the document without any images.</question>
[SQL]:
| <SQL_QUERY>SELECT document_name FROM documents EXCEPT SELECT t1.document_name FROM documents AS t1 JOIN document_sections AS t2 ON t1.document_code = t2.document_code JOIN document_sections_images AS t3 ON t2.section_id = t3.section_id</SQL_QUERY> | document_management | SELECT document_name FROM documents EXCEPT SELECT t1.document_name FROM documents AS t1 JOIN document_sections AS t2 ON t1.document_code = t2.document_code JOIN document_sections_images AS t3 ON t2.section_id = t3.section_id | Find names of the document without any images. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of documents that do not have any images?</question>
[SQL]:
| <SQL_QUERY>SELECT document_name FROM documents EXCEPT SELECT t1.document_name FROM documents AS t1 JOIN document_sections AS t2 ON t1.document_code = t2.document_code JOIN document_sections_images AS t3 ON t2.section_id = t3.section_id</SQL_QUERY> | document_management | SELECT document_name FROM documents EXCEPT SELECT t1.document_name FROM documents AS t1 JOIN document_sections AS t2 ON t1.document_code = t2.document_code JOIN document_sections_images AS t3 ON t2.section_id = t3.section_id | What are the names of documents that do not have any images? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of the document with the most number of sections?</question>
[SQL]:
| <SQL_QUERY>SELECT t1.document_name FROM documents AS t1 JOIN document_sections AS t2 ON t1.document_code = t2.document_code GROUP BY t1.document_code ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | document_management | SELECT t1.document_name FROM documents AS t1 JOIN document_sections AS t2 ON t1.document_code = t2.document_code GROUP BY t1.document_code ORDER BY count(*) DESC LIMIT 1 | What is the name of the document with the most number of sections? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the name of the document that has the most sections.</question>
[SQL]:
| <SQL_QUERY>SELECT t1.document_name FROM documents AS t1 JOIN document_sections AS t2 ON t1.document_code = t2.document_code GROUP BY t1.document_code ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | document_management | SELECT t1.document_name FROM documents AS t1 JOIN document_sections AS t2 ON t1.document_code = t2.document_code GROUP BY t1.document_code ORDER BY count(*) DESC LIMIT 1 | Return the name of the document that has the most sections. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List all the document names which contains "CV".</question>
[SQL]:
| <SQL_QUERY>SELECT document_name FROM documents WHERE document_name LIKE "%CV%"</SQL_QUERY> | document_management | SELECT document_name FROM documents WHERE document_name LIKE "%CV%" | List all the document names which contains "CV". | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of documents that contain the substring "CV"?</question>
[SQL]:
| <SQL_QUERY>SELECT document_name FROM documents WHERE document_name LIKE "%CV%"</SQL_QUERY> | document_management | SELECT document_name FROM documents WHERE document_name LIKE "%CV%" | What are the names of documents that contain the substring "CV"? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many users are logged in?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM users WHERE user_login = 1</SQL_QUERY> | document_management | SELECT count(*) FROM users WHERE user_login = 1 | How many users are logged in? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of users that are logged in.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM users WHERE user_login = 1</SQL_QUERY> | document_management | SELECT count(*) FROM users WHERE user_login = 1 | Count the number of users that are logged in. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the description of the most popular role among the users that have logged in.</question>
[SQL]:
| <SQL_QUERY>SELECT role_description FROM ROLES WHERE role_code = (SELECT role_code FROM users WHERE user_login = 1 GROUP BY role_code ORDER BY count(*) DESC LIMIT 1)</SQL_QUERY> | document_management | SELECT role_description FROM ROLES WHERE role_code = (SELECT role_code FROM users WHERE user_login = 1 GROUP BY role_code ORDER BY count(*) DESC LIMIT 1) | Find the description of the most popular role among the users that have logged in. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the description of the most popular role among users that have logged in?</question>
[SQL]:
| <SQL_QUERY>SELECT role_description FROM ROLES WHERE role_code = (SELECT role_code FROM users WHERE user_login = 1 GROUP BY role_code ORDER BY count(*) DESC LIMIT 1)</SQL_QUERY> | document_management | SELECT role_description FROM ROLES WHERE role_code = (SELECT role_code FROM users WHERE user_login = 1 GROUP BY role_code ORDER BY count(*) DESC LIMIT 1) | What is the description of the most popular role among users that have logged in? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the average access count of documents with the least popular structure.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(access_count) FROM documents GROUP BY document_structure_code ORDER BY count(*) ASC LIMIT 1</SQL_QUERY> | document_management | SELECT avg(access_count) FROM documents GROUP BY document_structure_code ORDER BY count(*) ASC LIMIT 1 | Find the average access count of documents with the least popular structure. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average access count of documents that have the least common structure?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(access_count) FROM documents GROUP BY document_structure_code ORDER BY count(*) ASC LIMIT 1</SQL_QUERY> | document_management | SELECT avg(access_count) FROM documents GROUP BY document_structure_code ORDER BY count(*) ASC LIMIT 1 | What is the average access count of documents that have the least common structure? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List all the image name and URLs in the order of their names.</question>
[SQL]:
| <SQL_QUERY>SELECT image_name , image_url FROM images ORDER BY image_name</SQL_QUERY> | document_management | SELECT image_name , image_url FROM images ORDER BY image_name | List all the image name and URLs in the order of their names. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names and urls of images, sorted alphabetically?</question>
[SQL]:
| <SQL_QUERY>SELECT image_name , image_url FROM images ORDER BY image_name</SQL_QUERY> | document_management | SELECT image_name , image_url FROM images ORDER BY image_name | What are the names and urls of images, sorted alphabetically? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of users in each role.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) , role_code FROM users GROUP BY role_code</SQL_QUERY> | document_management | SELECT count(*) , role_code FROM users GROUP BY role_code | Find the number of users in each role. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the different role codes for users, and how many users have each?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) , role_code FROM users GROUP BY role_code</SQL_QUERY> | document_management | SELECT count(*) , role_code FROM users GROUP BY role_code | What are the different role codes for users, and how many users have each? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What document types have more than 2 corresponding documents?</question>
[SQL]:
| <SQL_QUERY>SELECT document_type_code FROM documents GROUP BY document_type_code HAVING count(*) > 2</SQL_QUERY> | document_management | SELECT document_type_code FROM documents GROUP BY document_type_code HAVING count(*) > 2 | What document types have more than 2 corresponding documents? | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text);</schema>"
<primary_keys>[Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id</primary_keys>"
<foreign_keys>[Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Give the codes of document types that have more than 2 corresponding documents.</question>
[SQL]:
| <SQL_QUERY>SELECT document_type_code FROM documents GROUP BY document_type_code HAVING count(*) > 2</SQL_QUERY> | document_management | SELECT document_type_code FROM documents GROUP BY document_type_code HAVING count(*) > 2 | Give the codes of document types that have more than 2 corresponding documents. | [Schema (values) (types)]: | document_management | Roles : role_code (text) , role_description (text) | Users : user_id (text) , role_code (text) , user_name (text) , user_login (number) , password (text) | Document_Structures : document_structure_code (text) , parent_document_structure_code (text) , document_structure_description (text) | Functional_Areas : functional_area_code (text) , parent_functional_area_code (text) , functional_area_description (text) | Images : image_id (text) , image_alt_text (text) , image_name (text) , image_url (number) | Documents : document_code (text) , document_structure_code (text) , document_type_code (text) , access_count (number) , document_name (text) | Document_Functional_Areas : document_code (text) , functional_area_code (text) | Document_Sections : section_id (text) , document_code (text) , section_sequence (text) , section_code (number) , section_title (text) | Document_Sections_Images : section_id (text) , image_id (text); | [Primary Keys]: roles : role_code, users : user_id, document_structures : document_structure_code, functional_areas : functional_area_code, images : image_id, documents : document_code, document_functional_areas : section_id, document_sections : section_id | [Foreign Keys]: users : role_code = roles : role_code | documents : document_structure_code = document_structures : document_structure_code | document_functional_areas : functional_area_code = functional_areas : functional_area_code | document_functional_areas : document_code = documents : document_code | document_sections : document_code = documents : document_code | document_sections_images : image_id = images : image_id | document_sections_images : section_id = document_sections : section_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many companies are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM Companies</SQL_QUERY> | company_office | SELECT count(*) FROM Companies | How many companies are there? | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of companies.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM Companies</SQL_QUERY> | company_office | SELECT count(*) FROM Companies | Count the number of companies. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of companies in descending order of market value.</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM Companies ORDER BY Market_Value_billion DESC</SQL_QUERY> | company_office | SELECT name FROM Companies ORDER BY Market_Value_billion DESC | List the names of companies in descending order of market value. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Sort the company names in descending order of the company's market value.</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM Companies ORDER BY Market_Value_billion DESC</SQL_QUERY> | company_office | SELECT name FROM Companies ORDER BY Market_Value_billion DESC | Sort the company names in descending order of the company's market value. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of companies whose headquarters are not "USA"?</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM Companies WHERE Headquarters != 'USA'</SQL_QUERY> | company_office | SELECT name FROM Companies WHERE Headquarters != 'USA' | What are the names of companies whose headquarters are not "USA"? | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the names of the companies whose headquarters are not located in "USA".</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM Companies WHERE Headquarters != 'USA'</SQL_QUERY> | company_office | SELECT name FROM Companies WHERE Headquarters != 'USA' | Find the names of the companies whose headquarters are not located in "USA". | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the name and assets of each company, sorted in ascending order of company name?</question>
[SQL]:
| <SQL_QUERY>SELECT name , Assets_billion FROM Companies ORDER BY name ASC</SQL_QUERY> | company_office | SELECT name , Assets_billion FROM Companies ORDER BY name ASC | What are the name and assets of each company, sorted in ascending order of company name? | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name and assets of each company in ascending order of company name.</question>
[SQL]:
| <SQL_QUERY>SELECT name , Assets_billion FROM Companies ORDER BY name ASC</SQL_QUERY> | company_office | SELECT name , Assets_billion FROM Companies ORDER BY name ASC | List the name and assets of each company in ascending order of company name. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the average profits of companies?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Profits_billion) FROM Companies</SQL_QUERY> | company_office | SELECT avg(Profits_billion) FROM Companies | What are the average profits of companies? | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Compute the average profits companies make.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Profits_billion) FROM Companies</SQL_QUERY> | company_office | SELECT avg(Profits_billion) FROM Companies | Compute the average profits companies make. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the maximum and minimum sales of the companies whose industries are not "Banking".</question>
[SQL]:
| <SQL_QUERY>SELECT max(Sales_billion) , min(Sales_billion) FROM Companies WHERE Industry != "Banking"</SQL_QUERY> | company_office | SELECT max(Sales_billion) , min(Sales_billion) FROM Companies WHERE Industry != "Banking" | What are the maximum and minimum sales of the companies whose industries are not "Banking". | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the maximum and minimum sales of the companies that are not in the "Banking" industry.</question>
[SQL]:
| <SQL_QUERY>SELECT max(Sales_billion) , min(Sales_billion) FROM Companies WHERE Industry != "Banking"</SQL_QUERY> | company_office | SELECT max(Sales_billion) , min(Sales_billion) FROM Companies WHERE Industry != "Banking" | Find the maximum and minimum sales of the companies that are not in the "Banking" industry. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many different industries are the companies in?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT Industry) FROM Companies</SQL_QUERY> | company_office | SELECT count(DISTINCT Industry) FROM Companies | How many different industries are the companies in? | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of distinct company industries.</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT Industry) FROM Companies</SQL_QUERY> | company_office | SELECT count(DISTINCT Industry) FROM Companies | Count the number of distinct company industries. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of buildings in descending order of building height.</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM buildings ORDER BY Height DESC</SQL_QUERY> | company_office | SELECT name FROM buildings ORDER BY Height DESC | List the names of buildings in descending order of building height. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of buildings sorted in descending order of building height?</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM buildings ORDER BY Height DESC</SQL_QUERY> | company_office | SELECT name FROM buildings ORDER BY Height DESC | What are the names of buildings sorted in descending order of building height? | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the stories of the building with the largest height.</question>
[SQL]:
| <SQL_QUERY>SELECT Stories FROM buildings ORDER BY Height DESC LIMIT 1</SQL_QUERY> | company_office | SELECT Stories FROM buildings ORDER BY Height DESC LIMIT 1 | Find the stories of the building with the largest height. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the stories of highest building?</question>
[SQL]:
| <SQL_QUERY>SELECT Stories FROM buildings ORDER BY Height DESC LIMIT 1</SQL_QUERY> | company_office | SELECT Stories FROM buildings ORDER BY Height DESC LIMIT 1 | What is the stories of highest building? | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name of a building along with the name of a company whose office is in the building.</question>
[SQL]:
| <SQL_QUERY>SELECT T3.name , T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id</SQL_QUERY> | company_office | SELECT T3.name , T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id | List the name of a building along with the name of a company whose office is in the building. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each company, return the company name and the name of the building its office is located in.</question>
[SQL]:
| <SQL_QUERY>SELECT T3.name , T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id</SQL_QUERY> | company_office | SELECT T3.name , T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id | For each company, return the company name and the name of the building its office is located in. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of the buildings that have more than one company offices.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id GROUP BY T1.building_id HAVING COUNT(*) > 1</SQL_QUERY> | company_office | SELECT T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id GROUP BY T1.building_id HAVING COUNT(*) > 1 | Show the names of the buildings that have more than one company offices. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which buildings have more than one company offices? Give me the building names.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id GROUP BY T1.building_id HAVING COUNT(*) > 1</SQL_QUERY> | company_office | SELECT T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id GROUP BY T1.building_id HAVING COUNT(*) > 1 | Which buildings have more than one company offices? Give me the building names. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the name of the building that has the most company offices.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id GROUP BY T1.building_id ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | company_office | SELECT T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id GROUP BY T1.building_id ORDER BY COUNT(*) DESC LIMIT 1 | Show the name of the building that has the most company offices. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which building has the largest number of company offices? Give me the building name.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id GROUP BY T1.building_id ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | company_office | SELECT T2.name FROM Office_locations AS T1 JOIN buildings AS T2 ON T1.building_id = T2.id JOIN Companies AS T3 ON T1.company_id = T3.id GROUP BY T1.building_id ORDER BY COUNT(*) DESC LIMIT 1 | Which building has the largest number of company offices? Give me the building name. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Please show the names of the buildings whose status is "on-hold", in ascending order of stories.</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM buildings WHERE Status = "on-hold" ORDER BY Stories ASC</SQL_QUERY> | company_office | SELECT name FROM buildings WHERE Status = "on-hold" ORDER BY Stories ASC | Please show the names of the buildings whose status is "on-hold", in ascending order of stories. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the names of the buildings in "on-hold" status, and sort them in ascending order of building stories.</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM buildings WHERE Status = "on-hold" ORDER BY Stories ASC</SQL_QUERY> | company_office | SELECT name FROM buildings WHERE Status = "on-hold" ORDER BY Stories ASC | Find the names of the buildings in "on-hold" status, and sort them in ascending order of building stories. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Please show each industry and the corresponding number of companies in that industry.</question>
[SQL]:
| <SQL_QUERY>SELECT Industry , COUNT(*) FROM Companies GROUP BY Industry</SQL_QUERY> | company_office | SELECT Industry , COUNT(*) FROM Companies GROUP BY Industry | Please show each industry and the corresponding number of companies in that industry. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Whah are the name of each industry and the number of companies in that industry?</question>
[SQL]:
| <SQL_QUERY>SELECT Industry , COUNT(*) FROM Companies GROUP BY Industry</SQL_QUERY> | company_office | SELECT Industry , COUNT(*) FROM Companies GROUP BY Industry | Whah are the name of each industry and the number of companies in that industry? | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Please show the industries of companies in descending order of the number of companies.</question>
[SQL]:
| <SQL_QUERY>SELECT Industry FROM Companies GROUP BY Industry ORDER BY COUNT(*) DESC</SQL_QUERY> | company_office | SELECT Industry FROM Companies GROUP BY Industry ORDER BY COUNT(*) DESC | Please show the industries of companies in descending order of the number of companies. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Sort all the industries in descending order of the count of companies in each industry</question>
[SQL]:
| <SQL_QUERY>SELECT Industry FROM Companies GROUP BY Industry ORDER BY COUNT(*) DESC</SQL_QUERY> | company_office | SELECT Industry FROM Companies GROUP BY Industry ORDER BY COUNT(*) DESC | Sort all the industries in descending order of the count of companies in each industry | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the industry shared by the most companies.</question>
[SQL]:
| <SQL_QUERY>SELECT Industry FROM Companies GROUP BY Industry ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | company_office | SELECT Industry FROM Companies GROUP BY Industry ORDER BY COUNT(*) DESC LIMIT 1 | List the industry shared by the most companies. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which industry has the most companies?</question>
[SQL]:
| <SQL_QUERY>SELECT Industry FROM Companies GROUP BY Industry ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | company_office | SELECT Industry FROM Companies GROUP BY Industry ORDER BY COUNT(*) DESC LIMIT 1 | Which industry has the most companies? | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of buildings that have no company office.</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM buildings WHERE id NOT IN (SELECT building_id FROM Office_locations)</SQL_QUERY> | company_office | SELECT name FROM buildings WHERE id NOT IN (SELECT building_id FROM Office_locations) | List the names of buildings that have no company office. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which buildings do not have any company office? Give me the building names.</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM buildings WHERE id NOT IN (SELECT building_id FROM Office_locations)</SQL_QUERY> | company_office | SELECT name FROM buildings WHERE id NOT IN (SELECT building_id FROM Office_locations) | Which buildings do not have any company office? Give me the building names. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the industries shared by companies whose headquarters are "USA" and companies whose headquarters are "China".</question>
[SQL]:
| <SQL_QUERY>SELECT Industry FROM Companies WHERE Headquarters = "USA" INTERSECT SELECT Industry FROM Companies WHERE Headquarters = "China"</SQL_QUERY> | company_office | SELECT Industry FROM Companies WHERE Headquarters = "USA" INTERSECT SELECT Industry FROM Companies WHERE Headquarters = "China" | Show the industries shared by companies whose headquarters are "USA" and companies whose headquarters are "China". | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which industries have both companies with headquarter in "USA" and companies with headquarter in "China"?</question>
[SQL]:
| <SQL_QUERY>SELECT Industry FROM Companies WHERE Headquarters = "USA" INTERSECT SELECT Industry FROM Companies WHERE Headquarters = "China"</SQL_QUERY> | company_office | SELECT Industry FROM Companies WHERE Headquarters = "USA" INTERSECT SELECT Industry FROM Companies WHERE Headquarters = "China" | Which industries have both companies with headquarter in "USA" and companies with headquarter in "China"? | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of companies whose industry is "Banking" or "Conglomerate",</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM Companies WHERE Industry = "Banking" OR Industry = "Conglomerate"</SQL_QUERY> | company_office | SELECT count(*) FROM Companies WHERE Industry = "Banking" OR Industry = "Conglomerate" | Find the number of companies whose industry is "Banking" or "Conglomerate", | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many companies are in either "Banking" industry or "Conglomerate" industry?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM Companies WHERE Industry = "Banking" OR Industry = "Conglomerate"</SQL_QUERY> | company_office | SELECT count(*) FROM Companies WHERE Industry = "Banking" OR Industry = "Conglomerate" | How many companies are in either "Banking" industry or "Conglomerate" industry? | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the headquarters shared by more than two companies.</question>
[SQL]:
| <SQL_QUERY>SELECT Headquarters FROM Companies GROUP BY Headquarters HAVING COUNT(*) > 2</SQL_QUERY> | company_office | SELECT Headquarters FROM Companies GROUP BY Headquarters HAVING COUNT(*) > 2 | Show the headquarters shared by more than two companies. | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text);</schema>"
<primary_keys>[Primary Keys]: buildings : id, companies : id, office_locations : building_id</primary_keys>"
<foreign_keys>[Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which headquarter locations are used by more than 2 companies?</question>
[SQL]:
| <SQL_QUERY>SELECT Headquarters FROM Companies GROUP BY Headquarters HAVING COUNT(*) > 2</SQL_QUERY> | company_office | SELECT Headquarters FROM Companies GROUP BY Headquarters HAVING COUNT(*) > 2 | Which headquarter locations are used by more than 2 companies? | [Schema (values) (types)]: | company_office | buildings : id (text) , name (number) , city (text) , height (text) , stories (number) , status (number) | Companies : id (text) , name (number) , headquarters (text) , industry (text) , sales_billion (number) , profits_billion (number) , assets_billion (text) , market_value_billion (number) | Office_locations : building_id (text) , company_id (number) , move_in_year (text); | [Primary Keys]: buildings : id, companies : id, office_locations : building_id | [Foreign Keys]: office_locations : company_id = companies : id | office_locations : building_id = buildings : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many products are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM Products</SQL_QUERY> | solvency_ii | SELECT count(*) FROM Products | How many products are there? | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name of products in ascending order of price.</question>
[SQL]:
| <SQL_QUERY>SELECT Product_Name FROM Products ORDER BY Product_Price ASC</SQL_QUERY> | solvency_ii | SELECT Product_Name FROM Products ORDER BY Product_Price ASC | List the name of products in ascending order of price. | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names and type codes of products?</question>
[SQL]:
| <SQL_QUERY>SELECT Product_Name , Product_Type_Code FROM Products</SQL_QUERY> | solvency_ii | SELECT Product_Name , Product_Type_Code FROM Products | What are the names and type codes of products? | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the prices of the products named "Dining" or "Trading Policy".</question>
[SQL]:
| <SQL_QUERY>SELECT Product_Price FROM Products WHERE Product_Name = "Dining" OR Product_Name = "Trading Policy"</SQL_QUERY> | solvency_ii | SELECT Product_Price FROM Products WHERE Product_Name = "Dining" OR Product_Name = "Trading Policy" | Show the prices of the products named "Dining" or "Trading Policy". | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average price for products?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Product_Price) FROM Products</SQL_QUERY> | solvency_ii | SELECT avg(Product_Price) FROM Products | What is the average price for products? | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of the product with the highest price?</question>
[SQL]:
| <SQL_QUERY>SELECT Product_Name FROM Products ORDER BY Product_Price DESC LIMIT 1</SQL_QUERY> | solvency_ii | SELECT Product_Name FROM Products ORDER BY Product_Price DESC LIMIT 1 | What is the name of the product with the highest price? | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show different type codes of products and the number of products with each type code.</question>
[SQL]:
| <SQL_QUERY>SELECT Product_Type_Code , COUNT(*) FROM Products GROUP BY Product_Type_Code</SQL_QUERY> | solvency_ii | SELECT Product_Type_Code , COUNT(*) FROM Products GROUP BY Product_Type_Code | Show different type codes of products and the number of products with each type code. | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the most common type code across products.</question>
[SQL]:
| <SQL_QUERY>SELECT Product_Type_Code FROM Products GROUP BY Product_Type_Code ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | solvency_ii | SELECT Product_Type_Code FROM Products GROUP BY Product_Type_Code ORDER BY COUNT(*) DESC LIMIT 1 | Show the most common type code across products. | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the product type codes that have at least two products.</question>
[SQL]:
| <SQL_QUERY>SELECT Product_Type_Code FROM Products GROUP BY Product_Type_Code HAVING COUNT(*) >= 2</SQL_QUERY> | solvency_ii | SELECT Product_Type_Code FROM Products GROUP BY Product_Type_Code HAVING COUNT(*) >= 2 | Show the product type codes that have at least two products. | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the product type codes that have both products with price higher than 4500 and products with price lower than 3000.</question>
[SQL]:
| <SQL_QUERY>SELECT Product_Type_Code FROM Products WHERE Product_Price > 4500 INTERSECT SELECT Product_Type_Code FROM Products WHERE Product_Price < 3000</SQL_QUERY> | solvency_ii | SELECT Product_Type_Code FROM Products WHERE Product_Price > 4500 INTERSECT SELECT Product_Type_Code FROM Products WHERE Product_Price < 3000 | Show the product type codes that have both products with price higher than 4500 and products with price lower than 3000. | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of products and the number of events they are in.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Product_Name , COUNT(*) FROM Products AS T1 JOIN Products_in_Events AS T2 ON T1.Product_ID = T2.Product_ID GROUP BY T1.Product_Name</SQL_QUERY> | solvency_ii | SELECT T1.Product_Name , COUNT(*) FROM Products AS T1 JOIN Products_in_Events AS T2 ON T1.Product_ID = T2.Product_ID GROUP BY T1.Product_Name | Show the names of products and the number of events they are in. | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of products and the number of events they are in, sorted by the number of events in descending order.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Product_Name , COUNT(*) FROM Products AS T1 JOIN Products_in_Events AS T2 ON T1.Product_ID = T2.Product_ID GROUP BY T1.Product_Name ORDER BY COUNT(*) DESC</SQL_QUERY> | solvency_ii | SELECT T1.Product_Name , COUNT(*) FROM Products AS T1 JOIN Products_in_Events AS T2 ON T1.Product_ID = T2.Product_ID GROUP BY T1.Product_Name ORDER BY COUNT(*) DESC | Show the names of products and the number of events they are in, sorted by the number of events in descending order. | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of products that are in at least two events.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Product_Name FROM Products AS T1 JOIN Products_in_Events AS T2 ON T1.Product_ID = T2.Product_ID GROUP BY T1.Product_Name HAVING COUNT(*) >= 2</SQL_QUERY> | solvency_ii | SELECT T1.Product_Name FROM Products AS T1 JOIN Products_in_Events AS T2 ON T1.Product_ID = T2.Product_ID GROUP BY T1.Product_Name HAVING COUNT(*) >= 2 | Show the names of products that are in at least two events. | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of products that are in at least two events in ascending alphabetical order of product name.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Product_Name FROM Products AS T1 JOIN Products_in_Events AS T2 ON T1.Product_ID = T2.Product_ID GROUP BY T1.Product_Name HAVING COUNT(*) >= 2 ORDER BY T1.Product_Name</SQL_QUERY> | solvency_ii | SELECT T1.Product_Name FROM Products AS T1 JOIN Products_in_Events AS T2 ON T1.Product_ID = T2.Product_ID GROUP BY T1.Product_Name HAVING COUNT(*) >= 2 ORDER BY T1.Product_Name | Show the names of products that are in at least two events in ascending alphabetical order of product name. | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id</primary_keys>"
<foreign_keys>[Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of products that are not in any event.</question>
[SQL]:
| <SQL_QUERY>SELECT Product_Name FROM Products WHERE Product_ID NOT IN (SELECT Product_ID FROM Products_in_Events)</SQL_QUERY> | solvency_ii | SELECT Product_Name FROM Products WHERE Product_ID NOT IN (SELECT Product_ID FROM Products_in_Events) | List the names of products that are not in any event. | [Schema (values) (types)]: | solvency_ii | Addresses : address_id (text) , address_details (number) | Locations : location_id (text) , other_details (number) | Products : product_id (text) , product_type_code (number) , product_name (text) , product_price (number) | Parties : party_id (text) , party_details (number) | Assets : asset_id (text) , other_details (number) | Channels : channel_id (text) , other_details (number) | Finances : finance_id (text) , other_details (number) | Events : event_id (text) , address_id (number) , channel_id (text) , event_type_code (number) , finance_id (text) , location_id (number) | Products_in_Events : product_in_event_id (text) , event_id (number) , product_id (text) | Parties_in_Events : party_id (text) , event_id (number) , role_code (text) | Agreements : document_id (text) , event_id (number) | Assets_in_Events : asset_id (text) , event_id (number); | [Primary Keys]: addresses : address_id, locations : location_id, products : product_id, parties : party_id, assets : asset_id, channels : channel_id, finances : finance_id, events : event_id, products_in_events : product_in_event_id, parties_in_events : party_id, agreements : document_id, assets_in_events : asset_id | [Foreign Keys]: events : finance_id = finances : finance_id | events : address_id = addresses : address_id | events : location_id = locations : location_id | products_in_events : product_id = products : product_id | products_in_events : event_id = events : event_id | parties_in_events : event_id = events : event_id | parties_in_events : party_id = parties : party_id | agreements : event_id = events : event_id | assets_in_events : event_id = events : event_id | assets_in_events : event_id = events : event_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | entertainment_awards | festival_detail : festival_id (text) , festival_name (number) , chair_name (text) , location (text) , year (text) , num_of_audience (number) | artwork : artwork_id (text) , type (number) , name (text) | nomination : artwork_id (text) , festival_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: festival_detail : festival_id, artwork : artwork_id, nomination : artwork_id</primary_keys>"
<foreign_keys>[Foreign Keys]: nomination : festival_id = festival_detail : festival_id | nomination : artwork_id = artwork : artwork_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many artworks are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM artwork</SQL_QUERY> | entertainment_awards | SELECT count(*) FROM artwork | How many artworks are there? | [Schema (values) (types)]: | entertainment_awards | festival_detail : festival_id (text) , festival_name (number) , chair_name (text) , location (text) , year (text) , num_of_audience (number) | artwork : artwork_id (text) , type (number) , name (text) | nomination : artwork_id (text) , festival_id (number) , result (text); | [Primary Keys]: festival_detail : festival_id, artwork : artwork_id, nomination : artwork_id | [Foreign Keys]: nomination : festival_id = festival_detail : festival_id | nomination : artwork_id = artwork : artwork_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | entertainment_awards | festival_detail : festival_id (text) , festival_name (number) , chair_name (text) , location (text) , year (text) , num_of_audience (number) | artwork : artwork_id (text) , type (number) , name (text) | nomination : artwork_id (text) , festival_id (number) , result (text);</schema>"
<primary_keys>[Primary Keys]: festival_detail : festival_id, artwork : artwork_id, nomination : artwork_id</primary_keys>"
<foreign_keys>[Foreign Keys]: nomination : festival_id = festival_detail : festival_id | nomination : artwork_id = artwork : artwork_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name of artworks in ascending alphabetical order.</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM artwork ORDER BY Name ASC</SQL_QUERY> | entertainment_awards | SELECT Name FROM artwork ORDER BY Name ASC | List the name of artworks in ascending alphabetical order. | [Schema (values) (types)]: | entertainment_awards | festival_detail : festival_id (text) , festival_name (number) , chair_name (text) , location (text) , year (text) , num_of_audience (number) | artwork : artwork_id (text) , type (number) , name (text) | nomination : artwork_id (text) , festival_id (number) , result (text); | [Primary Keys]: festival_detail : festival_id, artwork : artwork_id, nomination : artwork_id | [Foreign Keys]: nomination : festival_id = festival_detail : festival_id | nomination : artwork_id = artwork : artwork_id |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.