@inproceedings{lovon-melgarejo-etal-2023-meerqat,
title = "{MEERQAT}-{IRIT} at {S}em{E}val-2023 Task 2: Leveraging Contextualized Tag Descriptors for Multilingual Named Entity Recognition",
author = "Lovon-Melgarejo, Jesus and
Moreno, Jose G. and
Besan{\c{c}}on, Romaric and
Ferret, Olivier and
Lechani, Lynda",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Da San Martino, Giovanni and
Tayyar Madabushi, Harish and
Kumar, Ritesh and
Sartori, Elisa},
booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.semeval-1.121",
doi = "10.18653/v1/2023.semeval-1.121",
pages = "878--884",
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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%0 Conference Proceedings
%T MEERQAT-IRIT at SemEval-2023 Task 2: Leveraging Contextualized Tag Descriptors for Multilingual Named Entity Recognition
%A Lovon-Melgarejo, Jesus
%A Moreno, Jose G.
%A Besançon, Romaric
%A Ferret, Olivier
%A Lechani, Lynda
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Da San Martino, Giovanni
%Y Tayyar Madabushi, Harish
%Y Kumar, Ritesh
%Y Sartori, Elisa
%S Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F lovon-melgarejo-etal-2023-meerqat
%X 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.
%R 10.18653/v1/2023.semeval-1.121
%U https://aclanthology.org/2023.semeval-1.121
%U https://doi.org/10.18653/v1/2023.semeval-1.121
%P 878-884
Markdown (Informal)
[MEERQAT-IRIT at SemEval-2023 Task 2: Leveraging Contextualized Tag Descriptors for Multilingual Named Entity Recognition](https://aclanthology.org/2023.semeval-1.121) (Lovon-Melgarejo et al., SemEval 2023)
ACL