README.md

---
pretty_name: FLARE-ES · TSA (Spanish)
license: other
license_name: public-source
language:
- es
task_categories:
- text-classification
size_categories:
- 1K<n<10K
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
  splits:
  - name: test
    num_bytes: 1316673
    num_examples: 3829
  download_size: 483832
  dataset_size: 1316673
extra_gated_heading: Request access to FLARE-ES · TSA (Spanish)
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 · TSA (Spanish)

📄 [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 | sentiment analysis |
| Original dataset | TSA (Pan et al., 2023) |
| Evaluation metric | F1, Accuracy |
| Source license | Public |
| Language | es |

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("TheFinAI/es-tsa", split="test")
print(ds[0])
```

## Example prompt

```text
Para el siguiente texto, por favor elija una etiqueta de clasificación de sentimiento (positivo, negativo, neutral)El sueldo medio alcanza máximos desde 2006, pero el 30% de los asalariados cobra menos de 1.336 euros
```

## Dataset Structure

| Split | Rows |
|---|---|
| `test` | 3,829 |

| Field | Description |
|---|---|
| `query` | Full instruction prompt given to the model |
| `answer` | Gold answer / label text |
| `text` | Raw input text (without instruction) |
| `choices` | Label space |
| `gold` | Index of the gold label in `choices` |

## 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 (TSA (Pan et al., 2023)):

```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},
}
```