An extensible massively multilingual lexical simplification pipeline dataset using the MultiLS framework

Shardlow, Matthew; Bott, Stefan Markus; Hayakawa, Akio; Saggion, Horacio

An extensible massively multilingual lexical simplification pipeline dataset using the MultiLS framework

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Citation

Shardlow M, Alva-Manchego F, Batista-Navarro R, Bott S, Calderon Ramirez S, Cardon R, et al. An extensible massively multilingual lexical simplification pipeline dataset using the MultiLS framework. In: Wilkens R, Cardon R, Todirascu A, Gala N, editors. Proceedings of the 3rd Workshop on Tools and Resources for People with REAding DIfficulties (READI) @ LREC-COLING 2024; 2024 May 20th; Torino, Italy. Brussels: ELRA and ICCL, 2024. p. 38–46.

Abstract

We present preliminary findings on the MultiLS dataset, developed in support of the 2024 Multilingual Lexical Simplification Pipeline (MLSP) Shared Task. This dataset currently comprises of 300 instances of lexical complexity prediction and lexical simplification across 10 languages. In this paper, we (1) describe the annotation protocol in support of the contribution of future datasets and (2) present summary statistics on the existing data that we have gathered. Multilingual lexical simplification can be used to support low-ability readers to engage with otherwise difficult texts in their native, often low-resourced, languages.

Description

Comunicació presentada a 3rd Workshop on Tools and Resources for People with REAding DIfficulties (READI) @ LREC-COLING 2024, celebrat el 20 de maig de 2024 a Torí, Itàlia.