Ferrés, DanielSaggion, Horacio2022-10-172022-10-172022Ferres D, Saggion H. ALEXSIS: a dataset for lexical simplification in spanish. In: Calzolari N, Béchet F, Blache P, Choukri K, Cieri C, Declerck T, Goggi S, Isahara H, Maegaard B, Mariani J, Mazo H, Odijk J, Piperidis S, editors. LREC 2022, 13th International Conference on Language Resources and Evaluation; 2022 June 20-25; Marseille, France. Paris: European Language Resources; 2022. p. 3582-94.http://hdl.handle.net/10230/54417Comunicació presentada a: LREC 2022, 13th International Conference on Language Resources and Evaluation, celebrat del 20 al 25 de juny de 2022 a Marsella, FrançaLexical Simplification is the process of reducing the lexical complexity of a text by replacing difficult words with easier to read (or understand) expressions while preserving the original information and meaning. In this paper we introduce ALEXSIS, a new dataset for this task, and we use ALEXSIS to benchmark Lexical Simplification systems in Spanish. The paper describes the evaluation of three kind of approaches to Lexical Simplification: a thesaurus-based approach, a single transformers-based approach, and a combination of transformers. We also report state of the art results on a previous Lexical Simplification dataset for Spanishapplication/pdfeng© European Language Resources Association (ELRA) These LREC2022 proceedings are licensed under a Creative Commons Attribution-NonCommercial 4.0 International Licenseinfo:eu-repo/semantics/conferenceObjectLexical SimplificationText SimplificationEvaluation Datasetinfo:eu-repo/semantics/openAccess