Task: NL2SQL (source dataset: Spider)

Natural language to SQL, also known as NL2SQL, is the problem of generating a SQL query that can be executed on a input table, for a given natural language question.

You will be given an input table called "table" in the markdown format, as well as a question. Your task is to generate an SQL query that can be executed on the input table to answer the question.

Please ensure that the generated SQL only return relevant columns being specifically asked in the question (e.g., in SQL please don't return more than one columns in SELECT if only one column is needed to answer the given question, and similarly please refrain from using SELECT * unless the entire row is needed to answer the question).
 
When generating SQL code, please use the SQLite syntax to ensure that your SQL is executable on SQLite3. Use only columns that are present in the table, always use quotes around your column and table names (some column names have punctuation or special characters), and refer to the columns using the column-names exactly as they appear in the table, do not add or remove punctuation (underscore, slash, etc.)

No explanation, return the code only with the following markdown codeblock format : ```sql<SQL CODE>```. For example, ```sql
SELECT * FROM "table"
``` is a valid format.

Database:
e_commerce

Tables:

Table: Products
|   product_id |   parent_product_id | product_name    |   product_price | product_color   | product_size   | product_description   |
|-------------:|--------------------:|:----------------|----------------:|:----------------|:---------------|:----------------------|
|            1 |                   8 | Dell monitor    |          795.62 | Red             | Medium         | Latest model!         |
|            2 |                   3 | Dell keyboard   |          104    | Yellow          | Medium         | Keyboard for games!   |
|            3 |                   1 | iPhone6s        |          560.93 | Red             | Small          | Second hand!          |
|            4 |                   6 | iWatch          |          369.11 | Red             | Medium         | Designed for sports!  |
|            5 |                   2 | Lenovo keyboard |          382.67 | Yellow          | Medium         | Work smartly!         |


Table: Customers
|   customer_id | gender_code   | customer_first_name   | customer_middle_initial   | customer_last_name   | email_address                | login_name      | login_password       | phone_number         | address_line_1                   | town_city         | county                                       | country   |
|--------------:|:--------------|:----------------------|:--------------------------|:---------------------|:-----------------------------|:----------------|:---------------------|:---------------------|:---------------------------------|:------------------|:---------------------------------------------|:----------|
|             1 | Female        | Carmen                | K                         | Treutel              | pgulgowski@example.com       | murphy07        | 58952d0e0d28de32db3b | (253)336-6277        | 646 Herzog Key Suite 702         | Port Madonnahaven | Israel                                       | USA       |
|             2 | Male          | Jace                  | P                         | Mraz                 | zwisozk@example.org          | desmond.steuber | 7ba2e47aa0904d9fbdbf | 628-468-4228x5917    | 67899 Cassin Hollow Suite 071    | Port Korychester  | Palau                                        | USA       |
|             3 | Male          | Vickie                | B                         | Bergnaum             | herzog.imogene@example.org   | kihn.alfonso    | 83a1afbe21f5ca4cd2d5 | 633-223-0975         | 395 Christophe Trail             | Lornaland         | Moldova                                      | USA       |
|             4 | Male          | Laurianne             | C                         | Pfeffer              | columbus.hackett@example.net | alena46         | 877cbaac266ddb0a513f | (874)589-9823x696    | 14173 Alize Summit               | Jennyferchester   | Saint Vincent and the Grenadines             | USA       |
|             5 | Female        | Verner                | V                         | Schulist             | juliet11@example.net         | nanderson       | c3cf21ffb950845c7d39 | (067)124-1804        | 69426 Lewis Estates Suite 438    | Greenfelderberg   | South Georgia and the South Sandwich Islands | USA       |
|             6 | Female        | Zetta                 | S                         | Streich              | melody.schuppe@example.org   | rau.felipe      | 52a6ca3fc466757bd7da | +50(2)2537278491     | 4672 Dwight Valleys Apt. 607     | East Fritz        | Afghanistan                                  | USA       |
|             7 | Male          | Jailyn                | C                         | Murray               | nmarquardt@example.org       | vwehner         | 372350093217369391dd | +12(1)5491495825     | 0933 Mozelle Junctions Suite 416 | Cliftonberg       | Reunion                                      | USA       |
|             8 | Male          | Rozella               | S                         | Crooks               | gilbert21@example.com        | jcremin         | cdda0eefb860f58bd638 | 648.826.7415         | 0629 Clotilde Mission            | Ledaville         | Bangladesh                                   | USA       |
|             9 | Female        | David                 | T                         | West                 | qkoepp@example.org           | shanie45        | b4380163b21bf36d5326 | 1-852-557-5246x36659 | 76015 Zelma Glen Apt. 194        | Lake Claudiefort  | Maldives                                     | USA       |
|            10 | Unknown       | America               | N                         | Nitzsche             | gino.cruickshank@example.org | zsawayn         | 9df44b9e0843940e1e87 | (352)290-2941x800    | 983 Jamil Way Apt. 732           | Braunland         | Swaziland                                    | USA       |


Table: Customer_Payment_Methods
|   customer_id | payment_method_code   |
|--------------:|:----------------------|
|            15 | Direct Debit          |
|             1 | Direct Debit          |
|            10 | Direct Debit          |
|            13 | Credit Card           |
|             9 | Credit Card           |
|             8 | Credit Card           |
|            13 | Cheque                |
|            15 | Direct Debit          |
|             4 | Credit Card           |
|             7 | Credit Card           |


Table: Invoices
|   invoice_number | invoice_status_code   | invoice_date        |
|-----------------:|:----------------------|:--------------------|
|                1 | Paid                  | 2018-03-09 07:16:07 |
|                2 | Issued                | 2018-01-28 20:08:22 |
|                3 | Paid                  | 2018-02-13 02:16:55 |
|                4 | Issued                | 2018-03-11 02:04:42 |
|                5 | Paid                  | 2018-03-14 11:58:55 |
|                6 | Paid                  | 2018-02-19 22:12:45 |
|                7 | Paid                  | 2018-02-14 02:48:48 |
|                8 | Paid                  | 2018-03-20 00:29:12 |
|                9 | Issued                | 2018-02-17 13:52:46 |
|               10 | Issued                | 2018-02-17 11:18:32 |


Table: Orders
|   order_id |   customer_id | order_status_code   | date_order_placed   |
|-----------:|--------------:|:--------------------|:--------------------|
|          1 |             5 | Cancelled           | 2017-09-17 16:13:07 |
|          2 |            13 | Part Completed      | 2017-10-14 12:05:48 |
|          3 |            13 | Cancelled           | 2017-09-10 08:27:04 |
|          4 |            11 | Delivered           | 2018-03-19 21:48:59 |
|          5 |             4 | Delivered           | 2017-09-17 07:48:34 |
|          6 |             8 | Delivered           | 2018-03-07 15:34:19 |
|          7 |             4 | Part Completed      | 2017-12-02 13:40:02 |
|          8 |            15 | Part Completed      | 2018-03-01 04:18:28 |
|          9 |             1 | Part Completed      | 2018-03-01 05:25:55 |
|         10 |            15 | Part Completed      | 2017-09-25 14:30:23 |


Table: Order_Items
|   order_item_id |   product_id |   order_id | order_item_status_code   |
|----------------:|-------------:|-----------:|:-------------------------|
|               1 |            4 |          8 | Delivered                |
|               2 |            3 |          4 | Out of Stock             |
|               3 |            2 |          7 | Delivered                |
|               4 |            1 |         10 | Out of Stock             |
|               5 |            1 |          3 | Delivered                |
|               6 |            1 |         18 | Delivered                |
|               7 |            5 |          3 | Delivered                |
|               8 |            4 |         19 | Out of Stock             |
|               9 |            5 |         18 | Out of Stock             |
|              10 |            3 |          6 | Delivered                |


Table: Shipments
|   shipment_id |   order_id |   invoice_number |   shipment_tracking_number | shipment_date       |
|--------------:|-----------:|-----------------:|---------------------------:|:--------------------|
|             1 |          7 |                5 |                       6900 | 2018-02-28 00:04:11 |
|             2 |          6 |                2 |                       3499 | 2018-03-07 01:57:14 |
|             3 |          9 |                4 |                       5617 | 2018-03-18 22:23:19 |
|             4 |          8 |               14 |                       6074 | 2018-03-11 23:48:37 |
|             5 |         12 |                9 |                       3848 | 2018-02-25 21:42:52 |
|             6 |         15 |               15 |                       3335 | 2018-03-15 01:10:18 |
|             7 |         14 |                3 |                       8731 | 2018-03-14 16:21:03 |
|             8 |         12 |                5 |                       6804 | 2018-03-12 01:44:44 |
|             9 |         18 |                7 |                       4377 | 2018-03-20 01:23:34 |
|            10 |          4 |               13 |                       8149 | 2018-03-16 03:30:05 |


Table: Shipment_Items
|   shipment_id |   order_item_id |
|--------------:|----------------:|
|             4 |               4 |
|             7 |              14 |
|            15 |               9 |
|             8 |              14 |
|             9 |              15 |
|             6 |              14 |


Question: List all the distinct product names, price and descriptions which are bought by female customers.

db_id: e_commerce
tables: name: Products
data: Products.csv
name: Customers
data: Customers.csv
name: Customer_Payment_Methods
data: Customer_Payment_Methods.csv
name: Invoices
data: Invoices.csv
name: Orders
data: Orders.csv
name: Order_Items
data: Order_Items.csv
name: Shipments
data: Shipments.csv
name: Shipment_Items
data: Shipment_Items.csv
label: SELECT DISTINCT T1.product_name ,  T1.product_price ,  T1.product_description FROM Products AS T1 JOIN Order_items AS T2 ON T1.product_id  =  T2.product_id JOIN Orders AS T3 ON T2.order_id  =  T3.order_id JOIN Customers AS T4 ON T3.customer_id  =  T4.customer_id WHERE T4.gender_code  =  'Female'
sqlite_path: $MMTU_HOME/data_sqlite/spider/spider_data/test_database/e_commerce/e_commerce.sqlite