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FLARE-ES · TSA (Spanish)

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

Quick Start

from datasets import load_dataset

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

Example prompt

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)):

@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},
}
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