##Instruction:
Database: sakila_1
Total Tables: 16
Total Columns: 89

Table Schemas:

sakila_1 contains tables such as actor, address, category, city, country, customer, film, film_actor, film_category, film_text, inventory, language, payment, rental, staff, store.
Table actor has columns such as actor_id, first_name, last_name, last_update.
actor_id is the primary key.
Table address has columns such as address_id, address, address2, district, city_id, postal_code, phone, last_update.
address_id is the primary key.
Table category has columns such as category_id, name, last_update.
category_id is the primary key.
Table city has columns such as city_id, city, country_id, last_update.
city_id is the primary key.
Table country has columns such as country_id, country, last_update.
country_id is the primary key.
Table customer has columns such as customer_id, store_id, first_name, last_name, email, address_id, active, create_date, last_update.
customer_id is the primary key.
Table film has columns such as film_id, title, description, release_year, language_id, original_language_id, rental_duration, rental_rate, length, replacement_cost, rating, special_features, last_update.
film_id is the primary key.
Table film_actor has columns such as actor_id, film_id, last_update.
actor_id is the primary key.
Table film_category has columns such as film_id, category_id, last_update.
film_id is the primary key.
Table film_text has columns such as film_id, title, description.
film_id is the primary key.
Table inventory has columns such as inventory_id, film_id, store_id, last_update.
inventory_id is the primary key.
Table language has columns such as language_id, name, last_update.
language_id is the primary key.
Table payment has columns such as payment_id, customer_id, staff_id, rental_id, amount, payment_date, last_update.
payment_id is the primary key.
Table rental has columns such as rental_id, rental_date, inventory_id, customer_id, return_date, staff_id, last_update.
rental_id is the primary key.
Table staff has columns such as staff_id, first_name, last_name, address_id, picture, email, store_id, active, username, password, last_update.
staff_id is the primary key.
Table store has columns such as store_id, manager_staff_id, address_id, last_update.
store_id is the primary key.
The city_id of address is the foreign key of city_id of city.
The country_id of city is the foreign key of country_id of country.
The store_id of customer is the foreign key of store_id of store.
The address_id of customer is the foreign key of address_id of address.
The original_language_id of film is the foreign key of language_id of language.
The language_id of film is the foreign key of language_id of language.
The film_id of film_actor is the foreign key of film_id of film.
The actor_id of film_actor is the foreign key of actor_id of actor.
The category_id of film_category is the foreign key of category_id of category.
The film_id of film_category is the foreign key of film_id of film.
The film_id of inventory is the foreign key of film_id of film.
The store_id of inventory is the foreign key of store_id of store.
The staff_id of payment is the foreign key of staff_id of staff.
The customer_id of payment is the foreign key of customer_id of customer.
The rental_id of payment is the foreign key of rental_id of rental.
The customer_id of rental is the foreign key of customer_id of customer.
The inventory_id of rental is the foreign key of inventory_id of inventory.
The staff_id of rental is the foreign key of staff_id of staff.
The address_id of staff is the foreign key of address_id of address.
The address_id of store is the foreign key of address_id of address.
The manager_staff_id of store is the foreign key of staff_id of staff.

##Role Access Policy (Column-Level):
Role: DataOperator_1
Accessible Columns:
  - actor: actor_id, last_name
  - address: address, address2, city_id, district, phone, postal_code
  - category: category_id, name
  - city: * (all columns)
  - country: country, country_id
  - customer: active, address_id, create_date, email
  - film: * (all columns)
  - film_actor: * (all columns)
  - film_category: category_id, film_id
  - film_text: title
  - inventory: film_id, last_update
  - language: name
  - payment: amount, last_update, payment_date, payment_id, staff_id
  - rental: * (all columns)
  - staff: * (all columns)
  - store: * (all columns)

Question: Return the titles of films that include 'Deleted Scenes' in their special feature section.
Answer: SELECT title FROM film WHERE special_features LIKE '%Deleted Scenes%'
Permission: allowed (All required columns are permitted)
Gold SQL: SELECT title FROM film WHERE special_features LIKE '%Deleted Scenes%'