Investigating NP-Chunking with Universal Dependencies for English

Ophélie Lacroix


Abstract
Chunking is a pre-processing task generally dedicated to improving constituency parsing. In this paper, we want to show that universal dependency (UD) parsing can also leverage the information provided by the task of chunking even though annotated chunks are not provided with universal dependency trees. In particular, we introduce the possibility of deducing noun-phrase (NP) chunks from universal dependencies, focusing on English as a first example. We then demonstrate how the task of NP-chunking can benefit PoS-tagging in a multi-task learning setting – comparing two different strategies – and how it can be used as a feature for dependency parsing in order to learn enriched models.
Anthology ID:
W18-6010
Volume:
Proceedings of the Second Workshop on Universal Dependencies (UDW 2018)
Month:
November
Year:
2018
Address:
Brussels, Belgium
Editors:
Marie-Catherine de Marneffe, Teresa Lynn, Sebastian Schuster
Venue:
UDW
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
85–90
Language:
URL:
https://aclanthology.org/W18-6010
DOI:
10.18653/v1/W18-6010
Bibkey:
Cite (ACL):
Ophélie Lacroix. 2018. Investigating NP-Chunking with Universal Dependencies for English. In Proceedings of the Second Workshop on Universal Dependencies (UDW 2018), pages 85–90, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Investigating NP-Chunking with Universal Dependencies for English (Lacroix, UDW 2018)
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PDF:
https://preview.aclanthology.org/improve-issue-templates/W18-6010.pdf