Abstract
Lexical 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 Spanish.- Anthology ID:
- 2022.lrec-1.383
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 3582–3594
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.383
- DOI:
- Cite (ACL):
- Daniel Ferrés and Horacio Saggion. 2022. ALEXSIS: A Dataset for Lexical Simplification in Spanish. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 3582–3594, Marseille, France. European Language Resources Association.
- Cite (Informal):
- ALEXSIS: A Dataset for Lexical Simplification in Spanish (Ferrés & Saggion, LREC 2022)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2022.lrec-1.383.pdf
- Code
- lastus-taln-upf/alexsis