Datasets:

TheFinAI
/

en-ectsum-long

pretty_name: FinBen · ECTSum (long-context)
license: other
license_name: public-source
language:
  - en
task_categories:
  - summarization
size_categories:
  - n<1K
source_datasets:
  - extended
tags:
  - finance
  - benchmark
  - thefinai
  - finben
  - flare
configs:
  - config_name: default
    data_files:
      - split: test
        path: data/test-*
dataset_info:
  features:
    - name: id
      dtype: string
    - name: query
      dtype: string
    - name: answer
      dtype: string
    - name: text
      dtype: string
    - name: __index_level_0__
      dtype: int64
  splits:
    - name: test
      num_bytes: 12547939
      num_examples: 117
  download_size: 6437502
  dataset_size: 12547939
extra_gated_heading: Request access to FinBen · ECTSum (long-context)
extra_gated_description: >-
  This FinBen task 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 the license of the original source
  (Public) and to cite the FinBen paper and the original dataset 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 papers: checkbox

FinBen · ECTSum (long-context)

📄 Paper · 💻 Code · 🏆 Leaderboard · 🌐 The Fin AI

Part of FinBen — FinBen: A Holistic Financial Benchmark for Large Language Models (arXiv:2402.12659).

Long-context variant of flare-ectsum in FinBen.


Task	text summarization
Original dataset	ECTSum (Mukherjee et al., 2022)
Evaluation metric	ROUGE, BERTScore, BARTScore
Source license	Public
Language	en

Quick Start

from datasets import load_dataset

ds = load_dataset("TheFinAI/en-ectsum-long", split="test")
print(ds[0])

Example prompt

You are given a text that consists of multiple sentences. Your task is to perform abstractive summarization on this text. Use your understanding of the content to express the main ideas and crucial details in a shorter, coherent, and natural sounding text.
Text: Operator
Good morning and thank you for standing by. Welcome to the AbbVie first quarter 2024 earnings conference call. All participants …

Dataset Structure

Split	Rows
`test`	117

Field	Description
`id`	Example id
`query`	Full instruction prompt given to the model
`answer`	Gold answer / label text
`text`	Raw input text (without instruction)
`__index_level_0__`

License

The paper lists the original data as publicly available without a specific license (FinBen paper, Table 2); refer to the original source for its terms.

Citation

Please cite FinBen and the original dataset (ECTSum (Mukherjee et al., 2022)):

@misc{xie2024finbenholisticfinancialbenchmark,
      title={FinBen: A Holistic Financial Benchmark for Large Language Models},
      author={Qianqian Xie and Weiguang Han and Zhengyu Chen and Ruoyu Xiang and Xiao Zhang and Yueru He and Mengxi Xiao and Dong Li and Yongfu Dai and Duanyu Feng and Yijing Xu and Haoqiang Kang and Ziyan Kuang and Chenhan Yuan and Kailai Yang and Zheheng Luo and Tianlin Zhang and Zhiwei Liu and Guojun Xiong and Zhiyang Deng and Yuechen Jiang and Zhiyuan Yao and Haohang Li and Yangyang Yu and Gang Hu and Jiajia Huang and Xiao-Yang Liu and Alejandro Lopez-Lira and Benyou Wang and Yanzhao Lai and Hao Wang and Min Peng and Sophia Ananiadou and Jimin Huang},
      year={2024},
      eprint={2402.12659},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2402.12659},
}