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metadata
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 · 🌐 The Fin AI
Part of FLARE-ES — Dólares or Dollars? Unraveling the Bilingual Prowess of Financial LLMs Between Spanish and English (arXiv: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
from datasets import load_dataset
ds = load_dataset("TheFinAI/es-efpa", split="test")
print(ds[0])
Example prompt
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/)):
@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},
}