README.md

metadata

license: cc-by-sa-4.0
task_categories:
  - text-generation
dataset_info:
  features:
    - name: db_id
      dtype: string
    - name: question
      dtype: string
    - name: evidence
      dtype: string
    - name: SQL
      dtype: string
    - name: difficulty
      dtype: string
    - name: question_id
      dtype: int64
    - name: sql_constructs
      list: string
    - name: sql_complexity
      dtype: int64
    - name: sql_complexity_buckets
      dtype: string
    - name: sqlglot_schema
      dtype: string
    - name: table_in_sql
      list: string
    - name: column_in_sql
      list: string
    - name: columns_used_to_join_in_sql
      list: string
    - name: schema
      struct:
        - name: schema
          dtype: string
    - name: schema_no_exp
      struct:
        - name: schema
          dtype: string
  splits:
    - name: train
      num_bytes: 125258621
      num_examples: 9074
    - name: dev
      num_bytes: 18084535
      num_examples: 1528
    - name: minidev
      num_bytes: 6033291
      num_examples: 495
  download_size: 2000452
  dataset_size: 149376447
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: dev
        path: data/dev-*
      - split: minidev
        path: data/minidev-*

Dataset

This dataset is a polished version of the BIRD dataset. It was introduced in the paper Think2SQL: Reinforce LLM Reasoning Capabilities for Text2SQL.

It has been used to train the reasoning Text2SQL model simone-papicchio/Think2SQL-7B.

Please refer to the paper for further details.

License: CC BY-SA 4.0

Citation

@misc{papicchio2025think2sqlreinforcellmreasoning,
      title={Think2SQL: Reinforce LLM Reasoning Capabilities for Text2SQL}, 
      author={Simone Papicchio and Simone Rossi and Luca Cagliero and Paolo Papotti},
      year={2025},
      eprint={2504.15077},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2504.15077}, 
}