@inproceedings{shardlow-etal-2024-extensible,
title = "An Extensible Massively Multilingual Lexical Simplification Pipeline Dataset using the {M}ulti{LS} Framework",
author = "Shardlow, Matthew and
Alva-Manchego, Fernando and
Batista-Navarro, Riza and
Bott, Stefan and
Calderon Ramirez, Saul and
Cardon, R{\'e}mi and
Fran{\c{c}}ois, Thomas and
Hayakawa, Akio and
Horbach, Andrea and
Huelsing, Anna and
Ide, Yusuke and
Imperial, Joseph Marvin and
Nohejl, Adam and
North, Kai and
Occhipinti, Laura and
Per{\'e}z Rojas, Nelson and
Raihan, Nishat and
Ranasinghe, Tharindu and
Solis Salazar, Martin and
Zampieri, Marcos and
Saggion, Horacio",
editor = "Wilkens, Rodrigo and
Cardon, R{\'e}mi and
Todirascu, Amalia and
Gala, N{\'u}ria",
booktitle = "Proceedings of the 3rd Workshop on Tools and Resources for People with REAding DIfficulties (READI) @ LREC-COLING 2024",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.readi-1.4",
pages = "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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T An Extensible Massively Multilingual Lexical Simplification Pipeline Dataset using the MultiLS Framework
%A Shardlow, Matthew
%A Alva-Manchego, Fernando
%A Batista-Navarro, Riza
%A Bott, Stefan
%A Calderon Ramirez, Saul
%A Cardon, Rémi
%A François, Thomas
%A Hayakawa, Akio
%A Horbach, Andrea
%A Huelsing, Anna
%A Ide, Yusuke
%A Imperial, Joseph Marvin
%A Nohejl, Adam
%A North, Kai
%A Occhipinti, Laura
%A Peréz Rojas, Nelson
%A Raihan, Nishat
%A Ranasinghe, Tharindu
%A Solis Salazar, Martin
%A Zampieri, Marcos
%A Saggion, Horacio
%Y Wilkens, Rodrigo
%Y Cardon, Rémi
%Y Todirascu, Amalia
%Y Gala, Núria
%S Proceedings of the 3rd Workshop on Tools and Resources for People with REAding DIfficulties (READI) @ LREC-COLING 2024
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F shardlow-etal-2024-extensible
%X 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.
%U https://aclanthology.org/2024.readi-1.4
%P 38-46
Markdown (Informal)
[An Extensible Massively Multilingual Lexical Simplification Pipeline Dataset using the MultiLS Framework](https://aclanthology.org/2024.readi-1.4) (Shardlow et al., READI-WS 2024)
ACL
- Matthew Shardlow, Fernando Alva-Manchego, Riza Batista-Navarro, Stefan Bott, Saul Calderon Ramirez, Rémi Cardon, Thomas François, Akio Hayakawa, Andrea Horbach, Anna Huelsing, Yusuke Ide, Joseph Marvin Imperial, Adam Nohejl, Kai North, Laura Occhipinti, Nelson Peréz Rojas, Nishat Raihan, Tharindu Ranasinghe, Martin Solis Salazar, et al.. 2024. An Extensible Massively Multilingual Lexical Simplification Pipeline Dataset using the MultiLS Framework. In Proceedings of the 3rd Workshop on Tools and Resources for People with REAding DIfficulties (READI) @ LREC-COLING 2024, pages 38–46, Torino, Italia. ELRA and ICCL.