sharkiefff/RBAC-Text2SQL-Benchmark huggingface dataset:
##Instruction:
Database: match_season
Total Tables: 4
Total Columns: 21

Table Schemas:

match_season contains tables such as country, team, match_season, player.
Table country has columns such as Country_id, Country_name, Capital, Official_native_language.
Country_id is the primary key.
Table team has columns such as Team_id, Name.
Team_id is the primary key.
Table match_season has columns such as Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College.
Season is the primary key.
Table player has columns such as Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team.
Player_ID is the primary key.
The Team of match_season is the foreign key of Team_id of team.
The Country of match_season is the foreign key of Country_id of country.
The Team of player is the foreign key of Team_id of team.

##Role Access Policy (Column-Level):
Role: ScoutingAnalyst
Accessible Columns: country: Country_id, Country_name, Official_native_language; team: Team_id, Name; match_season: Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College; player: Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: How many players played each position?
Answer: SELECT POSITION ,  COUNT(*) FROM match_season GROUP BY POSITION
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT POSITION ,  COUNT(*) FROM match_season GROUP BY POSITION
##Instruction:
Database: match_season
Total Tables: 4
Total Columns: 21

Table Schemas:

match_season contains tables such as country, team, match_season, player.
Table country has columns such as Country_id, Country_name, Capital, Official_native_language.
Country_id is the primary key.
Table team has columns such as Team_id, Name.
Team_id is the primary key.
Table match_season has columns such as Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College.
Season is the primary key.
Table player has columns such as Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team.
Player_ID is the primary key.
The Team of match_season is the foreign key of Team_id of team.
The Country of match_season is the foreign key of Country_id of country.
The Team of player is the foreign key of Team_id of team.

##Role Access Policy (Column-Level):
Role: ScoutingAnalyst
Accessible Columns: country: Country_id, Country_name, Official_native_language; team: Team_id, Name; match_season: Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College; player: Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: Show the country names and the corresponding number of players.
Answer: SELECT Country_name ,  COUNT(*) FROM country AS T1 JOIN match_season AS T2 ON T1.Country_id  =  T2.Country GROUP BY T1.Country_name
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT Country_name ,  COUNT(*) FROM country AS T1 JOIN match_season AS T2 ON T1.Country_id  =  T2.Country GROUP BY T1.Country_name
##Instruction:
Database: match_season
Total Tables: 4
Total Columns: 21

Table Schemas:

match_season contains tables such as country, team, match_season, player.
Table country has columns such as Country_id, Country_name, Capital, Official_native_language.
Country_id is the primary key.
Table team has columns such as Team_id, Name.
Team_id is the primary key.
Table match_season has columns such as Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College.
Season is the primary key.
Table player has columns such as Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team.
Player_ID is the primary key.
The Team of match_season is the foreign key of Team_id of team.
The Country of match_season is the foreign key of Country_id of country.
The Team of player is the foreign key of Team_id of team.

##Role Access Policy (Column-Level):
Role: ScoutingAnalyst
Accessible Columns: country: Country_id, Country_name, Official_native_language; team: Team_id, Name; match_season: Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College; player: Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: How many players are from each country?
Answer: SELECT Country_name ,  COUNT(*) FROM country AS T1 JOIN match_season AS T2 ON T1.Country_id  =  T2.Country GROUP BY T1.Country_name
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT Country_name ,  COUNT(*) FROM country AS T1 JOIN match_season AS T2 ON T1.Country_id  =  T2.Country GROUP BY T1.Country_name
##Instruction:
Database: match_season
Total Tables: 4
Total Columns: 21

Table Schemas:

match_season contains tables such as country, team, match_season, player.
Table country has columns such as Country_id, Country_name, Capital, Official_native_language.
Country_id is the primary key.
Table team has columns such as Team_id, Name.
Team_id is the primary key.
Table match_season has columns such as Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College.
Season is the primary key.
Table player has columns such as Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team.
Player_ID is the primary key.
The Team of match_season is the foreign key of Team_id of team.
The Country of match_season is the foreign key of Country_id of country.
The Team of player is the foreign key of Team_id of team.

##Role Access Policy (Column-Level):
Role: ScoutingAnalyst
Accessible Columns: country: Country_id, Country_name, Official_native_language; team: Team_id, Name; match_season: Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College; player: Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: Return all players sorted by college in ascending alphabetical order.
Answer: SELECT player FROM match_season ORDER BY College ASC
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT player FROM match_season ORDER BY College ASC
##Instruction:
Database: match_season
Total Tables: 4
Total Columns: 21

Table Schemas:

match_season contains tables such as country, team, match_season, player.
Table country has columns such as Country_id, Country_name, Capital, Official_native_language.
Country_id is the primary key.
Table team has columns such as Team_id, Name.
Team_id is the primary key.
Table match_season has columns such as Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College.
Season is the primary key.
Table player has columns such as Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team.
Player_ID is the primary key.
The Team of match_season is the foreign key of Team_id of team.
The Country of match_season is the foreign key of Country_id of country.
The Team of player is the foreign key of Team_id of team.

##Role Access Policy (Column-Level):
Role: ScoutingAnalyst
Accessible Columns: country: Country_id, Country_name, Official_native_language; team: Team_id, Name; match_season: Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College; player: Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: What are all the players who played in match season, sorted by college in ascending alphabetical order?
Answer: SELECT player FROM match_season ORDER BY College ASC
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT player FROM match_season ORDER BY College ASC
##Instruction:
Database: match_season
Total Tables: 4
Total Columns: 21

Table Schemas:

match_season contains tables such as country, team, match_season, player.
Table country has columns such as Country_id, Country_name, Capital, Official_native_language.
Country_id is the primary key.
Table team has columns such as Team_id, Name.
Team_id is the primary key.
Table match_season has columns such as Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College.
Season is the primary key.
Table player has columns such as Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team.
Player_ID is the primary key.
The Team of match_season is the foreign key of Team_id of team.
The Country of match_season is the foreign key of Country_id of country.
The Team of player is the foreign key of Team_id of team.

##Role Access Policy (Column-Level):
Role: ScoutingAnalyst
Accessible Columns: country: Country_id, Country_name, Official_native_language; team: Team_id, Name; match_season: Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College; player: Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: Show the most common position of players in match seasons.
Answer: SELECT POSITION FROM match_season GROUP BY POSITION ORDER BY count(*) DESC LIMIT 1
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT POSITION FROM match_season GROUP BY POSITION ORDER BY count(*) DESC LIMIT 1
##Instruction:
Database: match_season
Total Tables: 4
Total Columns: 21

Table Schemas:

match_season contains tables such as country, team, match_season, player.
Table country has columns such as Country_id, Country_name, Capital, Official_native_language.
Country_id is the primary key.
Table team has columns such as Team_id, Name.
Team_id is the primary key.
Table match_season has columns such as Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College.
Season is the primary key.
Table player has columns such as Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team.
Player_ID is the primary key.
The Team of match_season is the foreign key of Team_id of team.
The Country of match_season is the foreign key of Country_id of country.
The Team of player is the foreign key of Team_id of team.

##Role Access Policy (Column-Level):
Role: ScoutingAnalyst
Accessible Columns: country: Country_id, Country_name, Official_native_language; team: Team_id, Name; match_season: Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College; player: Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: What is the position that is most common among players in match seasons?
Answer: SELECT POSITION FROM match_season GROUP BY POSITION ORDER BY count(*) DESC LIMIT 1
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT POSITION FROM match_season GROUP BY POSITION ORDER BY count(*) DESC LIMIT 1
##Instruction:
Database: match_season
Total Tables: 4
Total Columns: 21

Table Schemas:

match_season contains tables such as country, team, match_season, player.
Table country has columns such as Country_id, Country_name, Capital, Official_native_language.
Country_id is the primary key.
Table team has columns such as Team_id, Name.
Team_id is the primary key.
Table match_season has columns such as Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College.
Season is the primary key.
Table player has columns such as Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team.
Player_ID is the primary key.
The Team of match_season is the foreign key of Team_id of team.
The Country of match_season is the foreign key of Country_id of country.
The Team of player is the foreign key of Team_id of team.

##Role Access Policy (Column-Level):
Role: ScoutingAnalyst
Accessible Columns: country: Country_id, Country_name, Official_native_language; team: Team_id, Name; match_season: Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College; player: Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: Show the top 3 most common colleges of players in match seasons.
Answer: SELECT College FROM match_season GROUP BY College ORDER BY count(*) DESC LIMIT 3
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT College FROM match_season GROUP BY College ORDER BY count(*) DESC LIMIT 3
##Instruction:
Database: match_season
Total Tables: 4
Total Columns: 21

Table Schemas:

match_season contains tables such as country, team, match_season, player.
Table country has columns such as Country_id, Country_name, Capital, Official_native_language.
Country_id is the primary key.
Table team has columns such as Team_id, Name.
Team_id is the primary key.
Table match_season has columns such as Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College.
Season is the primary key.
Table player has columns such as Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team.
Player_ID is the primary key.
The Team of match_season is the foreign key of Team_id of team.
The Country of match_season is the foreign key of Country_id of country.
The Team of player is the foreign key of Team_id of team.

##Role Access Policy (Column-Level):
Role: ScoutingAnalyst
Accessible Columns: country: Country_id, Country_name, Official_native_language; team: Team_id, Name; match_season: Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College; player: Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: What are the three colleges from which the most players are from?
Answer: SELECT College FROM match_season GROUP BY College ORDER BY count(*) DESC LIMIT 3
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT College FROM match_season GROUP BY College ORDER BY count(*) DESC LIMIT 3
##Instruction:
Database: match_season
Total Tables: 4
Total Columns: 21

Table Schemas:

match_season contains tables such as country, team, match_season, player.
Table country has columns such as Country_id, Country_name, Capital, Official_native_language.
Country_id is the primary key.
Table team has columns such as Team_id, Name.
Team_id is the primary key.
Table match_season has columns such as Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College.
Season is the primary key.
Table player has columns such as Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team.
Player_ID is the primary key.
The Team of match_season is the foreign key of Team_id of team.
The Country of match_season is the foreign key of Country_id of country.
The Team of player is the foreign key of Team_id of team.

##Role Access Policy (Column-Level):
Role: ScoutingAnalyst
Accessible Columns: country: Country_id, Country_name, Official_native_language; team: Team_id, Name; match_season: Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College; player: Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: Show the name of colleges that have at least two players.
Answer: SELECT College FROM match_season GROUP BY College HAVING count(*)  >=  2
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT College FROM match_season GROUP BY College HAVING count(*)  >=  2
##Instruction:
Database: match_season
Total Tables: 4
Total Columns: 21

Table Schemas:

match_season contains tables such as country, team, match_season, player.
Table country has columns such as Country_id, Country_name, Capital, Official_native_language.
Country_id is the primary key.
Table team has columns such as Team_id, Name.
Team_id is the primary key.
Table match_season has columns such as Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College.
Season is the primary key.
Table player has columns such as Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team.
Player_ID is the primary key.
The Team of match_season is the foreign key of Team_id of team.
The Country of match_season is the foreign key of Country_id of country.
The Team of player is the foreign key of Team_id of team.

##Role Access Policy (Column-Level):
Role: ScoutingAnalyst
Accessible Columns: country: Country_id, Country_name, Official_native_language; team: Team_id, Name; match_season: Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College; player: Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: What are the names of all colleges that have two or more players?
Answer: SELECT College FROM match_season GROUP BY College HAVING count(*)  >=  2
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT College FROM match_season GROUP BY College HAVING count(*)  >=  2
##Instruction:
Database: match_season
Total Tables: 4
Total Columns: 21

Table Schemas:

match_season contains tables such as country, team, match_season, player.
Table country has columns such as Country_id, Country_name, Capital, Official_native_language.
Country_id is the primary key.
Table team has columns such as Team_id, Name.
Team_id is the primary key.
Table match_season has columns such as Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College.
Season is the primary key.
Table player has columns such as Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team.
Player_ID is the primary key.
The Team of match_season is the foreign key of Team_id of team.
The Country of match_season is the foreign key of Country_id of country.
The Team of player is the foreign key of Team_id of team.

##Role Access Policy (Column-Level):
Role: ScoutingAnalyst
Accessible Columns: country: Country_id, Country_name, Official_native_language; team: Team_id, Name; match_season: Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College; player: Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: Show the name of colleges that have at least two players in descending alphabetical order.
Answer: SELECT College FROM match_season GROUP BY College HAVING count(*)  >=  2 ORDER BY College DESC
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT College FROM match_season GROUP BY College HAVING count(*)  >=  2 ORDER BY College DESC
##Instruction:
Database: match_season
Total Tables: 4
Total Columns: 21

Table Schemas:

match_season contains tables such as country, team, match_season, player.
Table country has columns such as Country_id, Country_name, Capital, Official_native_language.
Country_id is the primary key.
Table team has columns such as Team_id, Name.
Team_id is the primary key.
Table match_season has columns such as Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College.
Season is the primary key.
Table player has columns such as Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team.
Player_ID is the primary key.
The Team of match_season is the foreign key of Team_id of team.
The Country of match_season is the foreign key of Country_id of country.
The Team of player is the foreign key of Team_id of team.

##Role Access Policy (Column-Level):
Role: ScoutingAnalyst
Accessible Columns: country: Country_id, Country_name, Official_native_language; team: Team_id, Name; match_season: Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College; player: Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: What are the names of colleges that have two or more players, listed in descending alphabetical order?
Answer: SELECT College FROM match_season GROUP BY College HAVING count(*)  >=  2 ORDER BY College DESC
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT College FROM match_season GROUP BY College HAVING count(*)  >=  2 ORDER BY College DESC
##Instruction:
Database: match_season
Total Tables: 4
Total Columns: 21

Table Schemas:

match_season contains tables such as country, team, match_season, player.
Table country has columns such as Country_id, Country_name, Capital, Official_native_language.
Country_id is the primary key.
Table team has columns such as Team_id, Name.
Team_id is the primary key.
Table match_season has columns such as Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College.
Season is the primary key.
Table player has columns such as Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team.
Player_ID is the primary key.
The Team of match_season is the foreign key of Team_id of team.
The Country of match_season is the foreign key of Country_id of country.
The Team of player is the foreign key of Team_id of team.

##Role Access Policy (Column-Level):
Role: ScoutingAnalyst
Accessible Columns: country: Country_id, Country_name, Official_native_language; team: Team_id, Name; match_season: Season, Player, Position, Country, Team, Draft_Pick_Number, Draft_Class, College; player: Player_ID, Player, Years_Played, Total_WL, Singles_WL, Doubles_WL, Team

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: What are the names of teams that do no have match season record?
Answer: SELECT Name FROM team WHERE Team_id NOT IN (SELECT Team FROM match_season)
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT Name FROM team WHERE Team_id NOT IN (SELECT Team FROM match_season)