| pretty_name: Ebisu JF-TE | |
| license: cc-by-4.0 | |
| language: | |
| - ja | |
| task_categories: | |
| - token-classification | |
| tags: | |
| - finance | |
| - benchmark | |
| - japanese | |
| - thefinai | |
| - ebisu | |
| extra_gated_heading: Request access to Ebisu JF-TE | |
| extra_gated_description: Ebisu JF-TE 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 Ebisu 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 | |
| # Ebisu JF-TE | |
| 📄 [Paper](https://arxiv.org/abs/2602.01479) · 💻 [Code](https://github.com/The-FinAI/Ebisu) · 🌐 [The Fin AI](https://thefin.ai) | |
| > Part of **Ebisu** — *Ebisu: Benchmarking Large Language Models in Japanese Finance* ([arXiv:2602.01479](https://arxiv.org/abs/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 | |
| ```python | |
| 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 | |
| ```bibtex | |
| @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}, | |
| } | |
| ``` | |