| --- |
| pretty_name: FLARE-ES · EFPA |
| license: other |
| license_name: public-source |
| language: |
| - es |
| task_categories: |
| - question-answering |
| size_categories: |
| - n<1K |
| source_datasets: |
| - extended |
| tags: |
| - finance |
| - benchmark |
| - thefinai |
| - flare-es |
| - flare |
| dataset_info: |
| features: |
| - name: 'query:' |
| dtype: string |
| - name: answer |
| dtype: string |
| - name: text |
| dtype: string |
| - name: choices |
| sequence: string |
| - name: gold |
| dtype: int64 |
| - name: query |
| dtype: string |
| splits: |
| - name: test |
| num_bytes: 353055 |
| num_examples: 228 |
| download_size: 141839 |
| dataset_size: 353055 |
| extra_gated_heading: Request access to FLARE-ES · EFPA |
| extra_gated_description: This FLARE-ES 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 FLARE-ES 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 |
| --- |
| |
| # FLARE-ES · EFPA |
|
|
| 📄 [Paper](https://arxiv.org/abs/2402.07405) · 🌐 [The Fin AI](https://thefin.ai) |
|
|
| > Part of **FLARE-ES** — *Dólares or Dollars? Unraveling the Bilingual Prowess of Financial LLMs Between Spanish and English* ([arXiv:2402.07405](https://arxiv.org/abs/2402.07405)). |
|
|
| | | | |
| |---|---| |
| | Task | question answering (exam questions) | |
| | Original dataset | EFPA (https://efpa-eu.org/) | |
| | Evaluation metric | F1, Accuracy | |
| | Source license | Public | |
| | Language | es | |
|
|
| ## Quick Start |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("TheFinAI/es-efpa", split="test") |
| print(ds[0]) |
| ``` |
|
|
| ## Example prompt |
|
|
| ```text |
| Lea cuidadosamente las preguntas y respuestas, y elija la que considere apropiada entre las tres opciones A, B ,C y D |
| Q: Los riesgos del cambio climático que afectan directamente a las empresas mediante el daño sobre activos o infraestructuras o indirectamente en la alteración de sus operaciones o actividades se denominan:,CHOICES: A: Riesgos de transición. ,B: Riesgos de adaptación. ,… |
| ``` |
|
|
| ## Dataset Structure |
|
|
| | Split | Rows | |
| |---|---| |
| | `test` | 228 | |
|
|
| | Field | Description | |
| |---|---| |
| | `query:` | | |
| | `answer` | Gold answer / label text | |
| | `text` | Raw input text (without instruction) | |
| | `choices` | Label space | |
| | `gold` | Index of the gold label in `choices` | |
| | `query` | Full instruction prompt given to the model | |
|
|
| ## License |
|
|
| The paper lists the original data as **publicly available** without a specific license (FLARE-ES paper, Tables 1-2); refer to the original source for its terms. |
|
|
| ## Citation |
|
|
| Please cite FLARE-ES and the original dataset (EFPA (https://efpa-eu.org/)): |
|
|
| ```bibtex |
| @misc{zhang2024dolaresdollarsunravelingbilingual, |
| title={D\'olares or Dollars? Unraveling the Bilingual Prowess of Financial LLMs Between Spanish and English}, |
| author={Xiao Zhang and Ruoyu Xiang and Chenhan Yuan and Duanyu Feng and Weiguang Han and Alejandro Lopez-Lira and Xiao-Yang Liu and Sophia Ananiadou and Min Peng and Jimin Huang and Qianqian Xie}, |
| year={2024}, |
| eprint={2402.07405}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CL}, |
| url={https://arxiv.org/abs/2402.07405}, |
| } |
| ``` |
|
|
