Cross-lingual Semantic Role Labelling with the ValPaL Database Knowledge

Chinmay Choudhary, Colm O’Riordan


Abstract
Cross-lingual Transfer Learning typically involves training a model on a high-resource sourcelanguage and applying it to a low-resource tar-get language. In this work we introduce a lexi-cal database calledValency Patterns Leipzig(ValPal)which provides the argument patterninformation about various verb-forms in mul-tiple languages including low-resource langua-ges. We also provide a framework to integratethe ValPal database knowledge into the state-of-the-art LSTM based model for cross-lingualsemantic role labelling. Experimental resultsshow that integrating such knowledge resultedin am improvement in performance of the mo-del on all the target languages on which it isevaluated.
Anthology ID:
2022.deelio-1.1
Volume:
Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures
Month:
May
Year:
2022
Address:
Dublin, Ireland and Online
Editors:
Eneko Agirre, Marianna Apidianaki, Ivan Vulić
Venue:
DeeLIO
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–10
Language:
URL:
https://aclanthology.org/2022.deelio-1.1
DOI:
10.18653/v1/2022.deelio-1.1
Bibkey:
Cite (ACL):
Chinmay Choudhary and Colm O’Riordan. 2022. Cross-lingual Semantic Role Labelling with the ValPaL Database Knowledge. In Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures, pages 1–10, Dublin, Ireland and Online. Association for Computational Linguistics.
Cite (Informal):
Cross-lingual Semantic Role Labelling with the ValPaL Database Knowledge (Choudhary & O’Riordan, DeeLIO 2022)
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PDF:
https://aclanthology.org/2022.deelio-1.1.pdf
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