Datasets:

TheFinAI
/

multi-polyfiqa-easy

language:
  - en
  - zh
  - ja
  - es
  - el
license: mit
size_categories:
  - n<1K
task_categories:
  - question-answering
  - table-question-answering
pretty_name: PolyFiQA-Easy
dataset_info:
  features:
    - name: task_id
      dtype: string
    - name: query
      dtype: string
    - name: question
      dtype: string
    - name: answer
      dtype: string
  splits:
    - name: test
      num_bytes: 5175349
      num_examples: 76
  download_size: 1660121
  dataset_size: 5175349
configs:
  - config_name: default
    data_files:
      - split: test
        path: data/test-*
tags:
  - finance
  - multilingual
  - benchmark
  - thefinai
  - multifinben
extra_gated_heading: Request access to PolyFiQA-Easy
extra_gated_description: >-
  PolyFiQA-Easy is released by The Fin AI for research. Access is granted
  automatically after you complete this short form.
extra_gated_button_content: Agree and access
extra_gated_prompt: >-
  By accessing this dataset you agree to its license and to cite the MultiFinBen
  paper in any resulting publication.
extra_gated_fields:
  Full name: text
  Affiliation: text
  Country: country
  Intended use:
    type: select
    options:
      - Research
      - Education
      - Commercial evaluation
      - Other
  I agree to the terms above and will cite the paper: checkbox

Dataset Card for PolyFiQA-Easy

📄 Paper · 💻 Code · 🌐 The Fin AI

Part of MultiFinBen — MultiFinBen: Benchmarking Large Language Models for Multilingual and Multimodal Financial Application (arXiv:2506.14028). Formerly TheFinAI/PolyFiQA-Easy (the old name redirects here). Harder variant: multi-polyfiqa-expert.

Dataset Description
Dataset Structure
Dataset Creation
Considerations for Using the Data
Additional Information

Dataset Description

Homepage: https://huggingface.co/collections/TheFinAI/multifinben-6826f6fc4bc13d8af4fab223
Repository: https://huggingface.co/datasets/TheFinAI/polyfiqa-easy
Paper: MultiFinBen: A Multilingual, Multimodal, and Difficulty-Aware Benchmark for Financial LLM Evaluation
Benchmark Code: FinBen Github
Leaderboard: https://huggingface.co/spaces/TheFinAI/Open-FinLLM-Leaderboard

Dataset Summary

PolyFiQA-Easy is a multilingual financial question-answering dataset designed to evaluate financial reasoning in a simplified setting. Each instance consists of a task identifier, a query prompt, an associated financial question, and the correct answer. The Easy split focuses on queries that can be answered with minimal document retrieval, making it ideal for low-latency or resource-constrained systems.

Supported Tasks and Leaderboards

Tasks:
- question-answering
- table-question-answering
Evaluation Metrics:
- ROUGE-1

Languages

English (en)
Chinese (zh)
Japanese (jp)
Spanish (es)
Greek (el)

Dataset Structure

Data Instances

Each instance in the dataset contains:

task_id: A unique identifier for the query-task pair.
query: A brief query statement from the financial domain.
question: The full question posed based on the query context.
answer: The correct answer string.

Data Fields

Field	Type	Description
task_id	string	Unique ID per task
query	string	Financial query (short form)
question	string	Full natural-language financial question
answer	string	Ground-truth answer to the question

Data Splits

Split	# Examples	Size (bytes)
test	76	5,175,349

Dataset Creation

Curation Rationale

PolyFiQA-Easy was curated to provide a lightweight yet robust benchmark for financial question answering with minimal retrieval burden. It aims to evaluate models’ reasoning on self-contained or short-context questions in finance.

Source Data

Initial Data Collection

The source data was derived from a diverse collection of English financial reports. Questions were derived from real-world financial scenarios and manually adapted to fit a concise QA format.

Source Producers

Data was created by researchers and annotators with backgrounds in finance, NLP, and data curation.

Annotations

Annotation Process

Questions and answers were authored and verified through a multi-step validation pipeline involving domain experts.

Annotators

A team of finance researchers and data scientists.

Personal and Sensitive Information

The dataset contains no personal or sensitive information. All content is synthetic or anonymized for safe usage.

Considerations for Using the Data

Social Impact of Dataset

PolyFiQA-Easy contributes to research in financial NLP by enabling multilingual evaluation under constrained settings.

Discussion of Biases

May over-represent English financial contexts.
Questions emphasize clarity and answerability over real-world ambiguity.

Other Known Limitations

Limited size (76 examples).
Focused on easy questions; may not generalize to complex reasoning tasks.

Additional Information

Dataset Curators

The FinAI Team

Licensing Information

License: Apache License 2.0

Citation Information

If you use this dataset, please cite:

@misc{peng2025multifinbenmultilingualmultimodaldifficultyaware,
      title={MultiFinBen: A Multilingual, Multimodal, and Difficulty-Aware Benchmark for Financial LLM Evaluation}, 
      author={Xueqing Peng and Lingfei Qian and Yan Wang and Ruoyu Xiang and Yueru He and Yang Ren and Mingyang Jiang and Jeff Zhao and Huan He and Yi Han and Yun Feng and Yuechen Jiang and Yupeng Cao and Haohang Li and Yangyang Yu and Xiaoyu Wang and Penglei Gao and Shengyuan Lin and Keyi Wang and Shanshan Yang and Yilun Zhao and Zhiwei Liu and Peng Lu and Jerry Huang and Suyuchen Wang and Triantafillos Papadopoulos and Polydoros Giannouris and Efstathia Soufleri and Nuo Chen and Guojun Xiong and Zhiyang Deng and Yijia Zhao and Mingquan Lin and Meikang Qiu and Kaleb E Smith and Arman Cohan and Xiao-Yang Liu and Jimin Huang and Alejandro Lopez-Lira and Xi Chen and Junichi Tsujii and Jian-Yun Nie and Sophia Ananiadou and Qianqian Xie},
      year={2025},
      eprint={2506.14028},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2506.14028}, 
}