ISEP_Presidency_University at MLSP 2024 Shared Task: Using GPT-3.5 to Generate Substitutes for Lexical Simplification

Benjamin Dutilleul, Mathis Debaillon, Sandeep Mathias

Abstract
Lexical substitute generation is a task where we generate substitutes for a given word to fit in the required context. It is one of the main steps for automatic lexical simplifcation. In this paper, we introduce an automatic lexical simplification system using the GPT-3 large language model. The system generates simplified candidate substitutions for complex words to aid readability and comprehension for the reader. The paper describes the system that we submitted for the Multilingual Lexical Simplification Pipeline Shared Task at the 2024 BEA Workshop. During the shared task, we experimented with Catalan, English, French, Italian, Portuguese, and German for the Lexical Simplification Shared Task. We achieved the best results in Catalan and Portuguese, and were runners-up in English, French and Italian. To further research in this domain, we also release our code upon acceptance of the paper.
Anthology ID:
2024.bea-1.54
Volume:
Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2024)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Ekaterina Kochmar, Marie Bexte, Jill Burstein, Andrea Horbach, Ronja Laarmann-Quante, Anaïs Tack, Victoria Yaneva, Zheng Yuan
Venue:
BEA
SIG:
SIGEDU
Publisher:
Association for Computational Linguistics
Note:
Pages:
605–609
Language:
URL:
https://aclanthology.org/2024.bea-1.54
DOI:
Bibkey:
Cite (ACL):
Benjamin Dutilleul, Mathis Debaillon, and Sandeep Mathias. 2024. ISEP_Presidency_University at MLSP 2024 Shared Task: Using GPT-3.5 to Generate Substitutes for Lexical Simplification. In Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2024), pages 605–609, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
ISEP_Presidency_University at MLSP 2024 Shared Task: Using GPT-3.5 to Generate Substitutes for Lexical Simplification (Dutilleul et al., BEA 2024)
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