English Evaluation Dataset
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FinBen · FSRL
📄 Paper · 💻 Code · 🏆 Leaderboard · 🌐 The Fin AI
Part of FinBen — FinBen: A Holistic Financial Benchmark for Large Language Models (arXiv:2402.12659).
| Task | textual analogy parsing |
| Original dataset | FSRL (Lamm et al., 2018) |
| Evaluation metric | F1, EM Accuracy |
| Source license | MIT License |
| Language | en |
Quick Start
from datasets import load_dataset
ds = load_dataset("TheFinAI/en-fsrl", split="test")
print(ds[0])
Example prompt
In the task of Textual Analogy Parsing (TAP), your job is to identify and label the semantic role of each token in a sentence. The labels can include 'O', 'I-QUANT', 'B-QUANT', 'I-TIME', 'B-TIME', 'I-MANNER', 'B-MANNER', 'I-THEME', 'B-THEME', 'I-VALUE', 'B-VALUE', 'I-WHOLE', 'B-WHOLE', 'I-LOCATION', 'B-LOCATION', 'I-AGENT', 'B-AGENT', 'I-CAUSE', 'B-CAUSE', 'I-SOURCE', 'B-SOURCE', 'I-REF_TIME', 'B-…
Dataset Structure
| Split | Rows |
|---|---|
test |
97 |
| Field | Description |
|---|---|
id |
Example id |
query |
Full instruction prompt given to the model |
answer |
Gold answer / label text |
text |
Raw input text (without instruction) |
label |
Gold label(s) |
token |
License
The original data is released under MIT License (FinBen paper, Table 2).
Citation
Please cite FinBen and the original dataset (FSRL (Lamm et al., 2018)):
@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},
}
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