MEERQAT-IRIT at SemEval-2023 task 2: Leveraging contextualized tag descriptors for multilingual named entity recognition - Recherche d’Information et Synthèse d’Information Access content directly
Conference Papers Year : 2023

MEERQAT-IRIT at SemEval-2023 task 2: Leveraging contextualized tag descriptors for multilingual named entity recognition

Abstract

This paper describes the system we submitted to the SemEval 2023 Task 2 Multilingual Complex Named Entity Recognition (MultiCoNER II) in four monolingual tracks (English, Spanish, French, and Portuguese). Considering the low context setting and the fine-grained taxonomy presented in this task, we propose a system that leverages the language model representations using hand-crafted tag descriptors. We explored how integrating the contextualized representations of tag descriptors with a language model can help improve the model performance for this task. We performed our evaluations on the development and test sets used in the task for the Practice Phase and the Evaluation Phase respectively.
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Dates and versions

hal-04350288 , version 1 (18-12-2023)

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Cite

Jesus Lovon, Jose G. Moreno, Romaric Besançon, Lynda Tamine, Olivier Ferret. MEERQAT-IRIT at SemEval-2023 task 2: Leveraging contextualized tag descriptors for multilingual named entity recognition. 17th International Workshop on Semantic Evaluation (SemEval 2023), Jul 2023, Toronto, Canada. pp.878-884, ⟨10.18653/v1/2023.semeval-1.121⟩. ⟨hal-04350288⟩
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