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A BERT’s Eye View: Identification of Irish Multiword Expressions Using Pre-trained Language Models

Proceedings of the 18th Workshop on Multiword Expressions @LREC2022

DOI:10.63317/48asawpxzkn2

Abstract

This paper reports on the investigation of using pre-trained language models for the identification of Irish verbal multiword expressions (vMWEs), comparing the results with the systems submitted for the PARSEME shared task edition 1.2. We compare the use of a monolingual BERT model for Irish (gaBERT) with multilingual BERT (mBERT), fine-tuned to perform MWE identification, presenting a series of experiments to explore the impact of hyperparameter tuning and dataset optimisation steps on these models. We compare the results of our optimised systems to those achieved by other systems submitted to the shared task, and present some best practices for minority languages addressing this task.

Details

Paper ID
lrec2022-ws-mwe-13
Pages
pp. 89-99
BibKey
walsh-etal-2022-berts
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
N/A
ISBN
N/A
Workshop
Proceedings of the 18th Workshop on Multiword Expressions @LREC2022
Location
undefined, undefined
Date
20 June 2022 25 June 2022

Authors

  • AW

    Abigail Walsh

  • TL

    Teresa Lynn

  • JF

    Jennifer Foster

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