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Datasets:
gplsi
/
discriminative_clearsim_es

Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Languages:
Spanish
Size:
10K - 100K
Libraries:
Datasets
pandas
License:
Dataset card Data Studio Files
xet
Community
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📘 DISCRIMINATIVE CLEARSIM_ES

This is the discriminative version of the clearsim_es corpus.

This dataset contains pairs and triplets of texts written in original language (TXT), facilitated language (FAC), and easy language (LF).

The dataset contains 13,953 text entries, grouped into 4,651 unique triplets (row_ids).

📂 Dataset Splits

The dataset is divided into four splits:

Split Description
train Main training set. Mostly contains triplets (TXT, FAC, LF). About 40% of its samples are already complete triplets.
extra_train Additional training data. Includes texts that complete some pairs found in the test split.
test Main evaluation set. Contains pairs of texts (some incomplete).
extra_test Additional evaluation data. Completes some triplets from the train split.

🧾 Column Descriptions

Column Type Description
row_id string Identifier of the original triplet. Texts with the same row_id belong to the same triplet.
type string Text type:
- TXT: original text
- FAC: facilitated version
- LF: easy language version
text string The textual content itself.

⚠️ Notes

  • Texts are aligned by row_id, but not every row_id has all three versions (TXT, FAC, LF).
  • The "extra" splits (extra_train and extra_test) provide partial completion of missing pairs or triplets between the main splits.

💰 Funding

This work is funded by the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the project Desarrollo de Modelos ALIA.

📚 Reference

Please cite this model using the following BibTeX format:

@misc{discriminative2025clearsimes,
  author       = {Maestre, Mar{\'\i}a Mir{\'o} and Espinosa Zaragoza, Isabel and Sep{\'u}lveda Torres, Robiert and Mu{\~n}oz Guillena, Rafael and Consuegra-Ayala, Juan Pablo},
  title        = {DISCRIMINATIVE\_CLEARSIM\_ES Dataset},
  year         = {2025},
  institution  = {Language and Information Systems Group (GPLSI) and Centro de Inteligencia Digital (CENID), University of Alicante (UA)},
  howpublished = {\url{https://huggingface.co/datasets/gplsi/discriminative_clearsim_es}}
}

⚠️ Disclaimer

Be aware that the data may contain biases or other unintended distortions. When third parties deploy systems or provide services based on this data, or use the data themselves, they bear the responsibility for mitigating any associated risks and ensuring compliance with applicable regulations, including those governing the use of Artificial Intelligence. The University of Alicante, as the owner and creator of the model, shall not be held liable for any outcomes resulting from third-party use.

📜 License

This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) licence.

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