Overview of CLEARS at IberLEF 2025Challenge for Plain Language and Easy-to-Read Adaptation for Spanish texts

  1. Botella-Gil, Beatriz
  2. Espinosa-Zaragoza, Isabel
  3. Bonet-Jover, Alba
  4. Madina, Margot
  5. Molino Pi˜nar, Lucas
  6. Moreda, Paloma
  7. Gonzalez-Dios, Itziar
  8. Martín-Valdivia, M. Teresa
  9. Ure˜na-López, L. Alfonso
Journal:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Year of publication: 2025

Issue Title: Procesamiento del Lenguaje Natural, Revista nº 75, septiembre de 2025

Issue: 75

Pages: 393-400

Type: Article

DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: Procesamiento del lenguaje natural

Abstract

This paper presents CLEARS, a shared task organized within the framework of the evaluation campaign for Natural Language Processing systems in Spanish and other Iberian languages, IberLEF 2025. The main objective of CLEARS is to investigate and develop automatic techniques for adapting Spanish texts to plain language and easy-to-read formats. Two subtasks are proposed: the first focuses on adapting texts to plain language format, while the second aims to produce easy-toread texts. CLEARS attracted participation from four teams in Subtask 1 and five teams in Subtask 2. Each team submitted their results and approaches, which are presented below.

Bibliographic References

  • AENOR, 2018. Lectura Fácil. Pautas y recomendaciones para la elaboración de documentos. AENOR Internacional SAU, Madrid.
  • Agüera-Marco, B. and I. Gonzalez-Dios. 2025. Lengclaro2023: A dataset of administrative texts in spanish with plain language adaptations. arXiv preprint arXiv:2506.05927.
  • Al Ajlouni, A. B., J. Li, and A. A. Mo’ataz. 2023. Towards a comprehensive metric for evaluating text simplification systems. In 2023 14th International Conference on Information and Communication Systems (ICICS), pages 1–6. IEEE, November.
  • Alva-Manchego, F., C. Scarton, and L. Specia. 2021. The (un) suitability of automatic evaluation metrics for text simplification. Computational Linguistics, 47(4):861–889.
  • Bott, S. and H. Saggion. 2012. Automatic simplification of spanish text for eaccessibility. In Computers Helping People with Special Needs: 13th International Conference, ICCHP 2012, Linz, Austria, July 11–13, 2012, Proceedings, Part I. Springer Berlin Heidelberg, pages 527–534.
  • Calzolari, N., K. Choukri, T. Declerck, S. Goggi, M. Grobelnik, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, and S. Piperidis, editors. 2016. Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16), Portoroˇz, Slovenia, May. European Language Resources Association (ELRA).
  • Espinosa-Zaragoza, I., J. Abreu-Salas, E. Lloret, P. M. Pozo, and M. Palomar. 2023. A review of research-based automatic text simplification tools. In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, pages 321–330, September.
  • Fernández-Huerta, J. 1959. Medidas sencillas de lecturabilidad. Consigna, (214):29–32.
  • González-Barba, J. ´ A., L. Chiruzzo, and S. M. Jiménez-Zafra. 2025. Overview of IberLEF 2025: Natural Language Processing Challenges for Spanish and other Iberian Languages. In Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2025), co-located with the 41st Conference of the Spanish Society for Natural Language Processing (SEPLN 2025), CEUR-WS. org.
  • Instituto Cervantes. 2022. El español: una lengua viva. informe 2022. Informe técnico, Instituto Cervantes.
  • Papineni, K., S. Roukos, T. Ward, and W. J. Zhu. 2002. Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting of the Association for Computational Linguistics, pages 311–318, July.
  • Prodigioso Volcán. 2020. Plain language in administrative texts in spanish. ¿habla claro la administración? Technical report, Prodigioso Volcán.
  • Saggion, H., S. Stajner, D. Ferrés, K. C. Sheang, M. Shardlow, K. North, and M. Zampieri. 2022. Findings of the TSAR-2022 shared task on multilingual lexical simplification. In S. Stajner, H. Saggion, D. Ferrés, M. Shardlow, K. C. Sheang, K. North, M. Zampieri, and W. Xu, editors, Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022), pages 271–283, Abu Dhabi, United Arab Emirates (Virtual), December. Association for Computational Linguistics.
  • Specia, L., S. K. Jauhar, and R. Mihalcea. 2012. Semeval-2012 task 1: English lexical simplification. In * SEM 2012: The First Joint Conference on Lexical and Computational Semantics–Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012), pages 347–355.
  • Sulem, E., O. Abend, and A. Rappoport. 2018. Semantic structural evaluation for text simplification. arXiv preprint arXiv:1810.05022.
  • Tascón, M. and E. Montolío. 2020. El derecho a entender: la comunicación clara, la mejor defensa de la ciudadanía. Los libros de la Catarata.
  • Xu, W., C. Napoles, E. Pavlick, Q. Chen, and C. Callison-Burch. 2016. Optimizing statistical machine translation for text simplification. Transactions of the Association for Computational Linguistics, 4:401–415.
  • Yaneva, V., K. North, P. Baldwin, L. A. Ha, S. Rezayi, Y. Zhou, S. Ray Choudhury, P. Harik, and B. Clauser. 2024. Findings from the first shared task on automated prediction of difficulty and response time for multiple-choice questions. In E. Kochmar, M. Bexte, J. Burstein, A. Horbach, R. Laarmann-Quante, A. Tack, V. Yaneva, and Z. Yuan, editors, Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2024), pages 470–482, Mexico City, Mexico, June. Association for Computational Linguistics.
  • Zhang, T., V. Kishore, F. Wu, K. Q. Weinberger, and Y. Artzi. 2020. Bertscore: Evaluating text generation with bert. arXiv preprint arXiv:1904.09675.
Data source: Dialnet