Datasets:

TheFinAI
/

jp-te

pretty_name: Ebisu JF-TE
license: cc-by-4.0
language:
  - ja
task_categories:
  - token-classification
tags:
  - finance
  - benchmark
  - japanese
  - thefinai
  - ebisu
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  automatically after you complete this short form.
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extra_gated_prompt: >-
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Ebisu JF-TE

📄 Paper · 💻 Code · 🌐 The Fin AI

Part of Ebisu — Ebisu: Benchmarking Large Language Models in Japanese Finance (arXiv:2602.01479). Formerly TheFinAI/JF-TE (the old name redirects here).

JF-TE (Japanese Financial Term Extraction) asks a model to extract financial terms — including nested nominal compounds — from Japanese corporate disclosures. The paper evaluates it with Maximal Financial Term F1 and HitRate@K for nested terms.

This public release contains 58 examples (train split, single jf_te.jsonl file).

Quick Start

from datasets import load_dataset

ds = load_dataset("TheFinAI/jp-te", split="train")
print(ds[0]["query"])
print(ds[0]["answer"])

Field	Description
`query`	Instruction prompt with the Japanese passage
`answer`	Gold financial terms (nested lists)
`id`	Example id

Citation

@misc{peng2026ebisubenchmarkinglargelanguage,
      title={Ebisu: Benchmarking Large Language Models in Japanese Finance}, 
      author={Xueqing Peng and Ruoyu Xiang and Fan Zhang and Mingzi Song and Mingyang Jiang and Yan Wang and Lingfei Qian and Taiki Hara and Yuqing Guo and Jimin Huang and Junichi Tsujii and Sophia Ananiadou},
      year={2026},
      eprint={2602.01479},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2602.01479}, 
}