FinQA Dataset (Processed)

Dataset Description

Dataset Summary

The FinQA dataset is designed for numerical reasoning over financial data, containing questions that require complex reasoning over tables and text from financial reports.

Dataset Statistics

Total examples: 8281
Training set size: 6624 examples
Test set size: 1657 examples

Dataset Structure

Each example contains:

Required columns:
- query: The question to be answered (derived directly from qa.question)
- context: Combined context including pre-text, table, and post-text, formatted with random section headers and separators for variety
- output: The execution answer (derived from qa.exe_ans)
Original FinQA fields:
- id: Unique example identifier
- pre_text: Text appearing before the table
- post_text: Text appearing after the table
- table: Tabular data in string format
- program: The reasoning program to derive the answer
- exe_ans: The execution result

Context Formation

The context field is created by concatenating:

Pre-text with a randomly selected header (e.g., "Background:", "Context:", "Pre-text:")
Table data with a randomly selected header (e.g., "Data Table:", "Tabular Data:", "Table:")
Post-text with a randomly selected header (e.g., "Additional Information:", "Follow-up:", "Post-table:")

These sections are joined using random separators (##,

, or --) to create variety.

Dataset Creation

Source Data

This dataset is derived from the FinQA dataset created by Chen et al. The original dataset is available at FinQA GitHub Repository.

Citation

@article{chen2021finqa,
  title={FinQA: A Dataset of Numerical Reasoning over Financial Data},
  author={Chen, Zhiyu and Chen, Wenhu and Smiley, Charese and Shah, Sameena and Borova, Iana and Langdon, Dylan and Moussa, Reema and Beane, Matt and Huang, Ting-Hao and Routledge, Bryan and Wang, William Yang},
  journal={Proceedings of EMNLP 2021},
  year={2021}
}

Licensing Information

This dataset is released under the MIT License, following the original FinQA dataset licensing terms.