You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 books
【Schema】
# Table: book_language
[
(language_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(language_code:TEXT, Examples: [eng, en-US, fre]),
(language_name:TEXT, Examples: [English])
]
# Table: country
[
(country_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Afghanistan, Netherlands Antilles, Albania])
]
# Table: customer
[
(customer_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(first_name:TEXT, Examples: [Ursola, Ruthanne, Reidar]),
(last_name:TEXT, Examples: [Purdy, Vatini, Turbitt]),
(email:TEXT)
]
# Table: order_history
[
(history_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(order_id:INTEGER, Examples: [1, 2, 3]),
(status_id:INTEGER, Examples: [1, 2, 3]),
(status_date:DATETIME, Examples: [2021-07-14 17:04:28])
]
# Table: book
[
(book_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(title:TEXT, Examples: [The World's First Love: Mary  Mother of God]),
(isbn13:TEXT, Examples: [8987059752, 20049130001, 23755004321]),
(language_id:INTEGER, Examples: [2, 1, 5]),
(num_pages:INTEGER, Examples: [276, 352, 128]),
(publication_date:DATE, Examples: [1996-09-01]),
(publisher_id:INTEGER, Examples: [1010, 1967, 1978])
]
# Table: book_author
[
(book_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(author_id:INTEGER, Primary Key, Examples: [1, 2, 3])
]
# Table: shipping_method
[
(method_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(method_name:TEXT, Examples: [Standard, Priority, Express]),
(cost:REAL, Examples: [5.9, 8.9, 11.9])
]
# Table: order_line
[
(line_id:INTEGER, Primary Key, Examples: [1024, 1025, 1026]),
(order_id:INTEGER, Examples: [2051, 899, 4994]),
(book_id:INTEGER, Examples: [10720, 10105, 6503]),
(price:REAL, Examples: [3.19, 1.24, 14.74])
]
# Table: address
[
(address_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(street_number:TEXT, Examples: [57, 86, 292]),
(street_name:TEXT, Examples: [Glacier Hill Avenue, Dottie Junction, Ramsey Avenue]),
(city:TEXT, Examples: [Torbat-e Jām, Beaumont, Cayambe]),
(country_id:INTEGER, Examples: [95, 37, 60])
]
# Table: publisher
[
(publisher_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(publisher_name:TEXT, Examples: [10/18, 1st Book Library, 1st World Library])
]
# Table: author
[
(author_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(author_name:TEXT, Examples: [A. Bartlett Giamatti, A. Elizabeth Delany, A. Merritt])
]
# Table: address_status
[
(status_id:INTEGER, Primary Key, Examples: [1, 2]),
(address_status:TEXT, Examples: [Active, Inactive])
]
# Table: cust_order
[
(order_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(order_date:DATETIME, Examples: [2021-07-14 10:47:19]),
(customer_id:INTEGER, Examples: [387, 1256, 1335]),
(shipping_method_id:INTEGER, Examples: [4, 2, 1]),
(dest_address_id:INTEGER, Examples: [1, 2, 3])
]
# Table: customer_address
[
(customer_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(address_id:INTEGER, Primary Key, Examples: [606, 266, 376]),
(status_id:INTEGER, Examples: [1, 2])
]
# Table: order_status
[
(status_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(status_value:TEXT, Examples: [Order Received, Pending Delivery, Delivery In Progress])
]
【Foreign keys】
order_history.status_id=order_status.status_id
order_history.order_id=cust_order.order_id
book.language_id=book_language.language_id
book.publisher_id=publisher.publisher_id
book_author.author_id=author.author_id
book_author.book_id=book.book_id
order_line.book_id=book.book_id
order_line.order_id=cust_order.order_id
address.country_id=country.country_id
cust_order.dest_address_id=address.address_id
cust_order.shipping_method_id=shipping_method.method_id
cust_order.customer_id=customer.customer_id
customer_address.address_id=address.address_id
customer_address.customer_id=customer.customer_id

    【Question】
    List all the authors named "George". author named 'George' refers to author_name = 'George%'

    【Evidence】
    author named 'George' refers to author_name = 'George%'

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT author_name FROM author WHERE author_name LIKE 'George%'