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:
cre_Doc_and_collections

Tables:

Table: Document_Subsets
|   Document_Subset_ID | Document_Subset_Name   | Document_Subset_Details   |
|---------------------:|:-----------------------|:--------------------------|
|                  171 | Best for 2000          |                           |
|                  183 | Best for 2001          |                           |
|                  216 | Best for 2002          |                           |
|                  488 | Best for 2003          |                           |
|                  535 | Best for 2004          |                           |
|                  547 | Best for 2005          |                           |
|                  640 | Best for 2006          |                           |
|                  653 | Best for 2007          |                           |


Table: Collection_Subsets
|   Collection_Subset_ID | Collection_Subset_Name   | Collecrtion_Subset_Details   |
|-----------------------:|:-------------------------|:-----------------------------|
|                    684 | UK album                 |                              |
|                    717 | US album                 |                              |
|                    741 | Canadian album           |                              |
|                    813 | History collection       |                              |
|                    851 | Art collection           |                              |
|                    981 | Top collection           |                              |
|                    997 | Fine set                 |                              |


Table: Document_Objects
|   Document_Object_ID |   Parent_Document_Object_ID | Owner   | Description        | Other_Details   |
|---------------------:|----------------------------:|:--------|:-------------------|:----------------|
|                    5 |                           5 | Ransom  | Ransom Collection  |                 |
|                    8 |                           9 | Marlin  | Marlin Collection  |                 |
|                    9 |                           9 | Braeden | Braeden Collection |                 |


Table: Collections
|   Collection_ID |   Parent_Collection_ID | Collection_Name   | Collection_Description   |
|----------------:|-----------------------:|:------------------|:-------------------------|
|               6 |                      6 | Best              |                          |
|               7 |                      6 | Nice              |                          |


Table: Documents_in_Collections
|   Document_Object_ID |   Collection_ID |
|---------------------:|----------------:|
|                    5 |               6 |
|                    5 |               7 |
|                    8 |               6 |
|                    8 |               7 |
|                    9 |               6 |
|                    9 |               7 |


Table: Document_Subset_Members
|   Document_Object_ID |   Related_Document_Object_ID |   Document_Subset_ID |
|---------------------:|-----------------------------:|---------------------:|
|                    5 |                            5 |                  547 |
|                    5 |                            8 |                  183 |
|                    5 |                            9 |                  653 |
|                    8 |                            5 |                  183 |
|                    8 |                            8 |                  653 |
|                    8 |                            9 |                  216 |
|                    9 |                            5 |                  171 |
|                    9 |                            8 |                  171 |


Table: Collection_Subset_Members
|   Collection_ID |   Related_Collection_ID |   Collection_Subset_ID |
|----------------:|------------------------:|-----------------------:|
|               6 |                       6 |                    717 |
|               6 |                       7 |                    981 |
|               7 |                       6 |                    851 |
|               7 |                       7 |                    851 |


Question: How many collections does each document belong to? List the count and the document id.

db_id: cre_Doc_and_collections
tables: name: Document_Subsets
data: Document_Subsets.csv
name: Collection_Subsets
data: Collection_Subsets.csv
name: Document_Objects
data: Document_Objects.csv
name: Collections
data: Collections.csv
name: Documents_in_Collections
data: Documents_in_Collections.csv
name: Document_Subset_Members
data: Document_Subset_Members.csv
name: Collection_Subset_Members
data: Collection_Subset_Members.csv
label: SELECT count(*) ,  T2.Document_Object_ID FROM Collections AS T1 JOIN Documents_in_Collections AS T2 ON T1.Collection_ID = T2.Collection_ID GROUP BY T2.Document_Object_ID
sqlite_path: $MMTU_HOME/data_sqlite/spider/spider_data/test_database/cre_Doc_and_collections/cre_Doc_and_collections.sqlite