Moosavi, N.S. orcid.org/0000-0002-8332-307X and Strube, M. (2017) Lexical features in coreference resolution: to be used with caution. In: Barzilay, R. and Kan, M.-Y., (eds.) Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics. Annual Meeting of the Association for Computational Linguistics (ACL 2017), 30 Jul - 04 Aug 2017, Vancouver, Canada. Association for Computational Linguistics , pp. 14-19. ISBN 9781945626760
Abstract
Lexical features are a major source of information in state-of-the-art coreference resolvers. Lexical features implicitly model some of the linguistic phenomena at a fine granularity level. They are especially useful for representing the context of mentions. In this paper we investigate a drawback of using many lexical features in state-of-the-art coreference resolvers. We show that if coreference resolvers mainly rely on lexical features, they can hardly generalize to unseen domains. Furthermore, we show that the current coreference resolution evaluation is clearly flawed by only evaluating on a specific split of a specific dataset in which there is a notable overlap between the training, development and test sets.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2017 Association for Computational Linguistics. Available under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Sep 2022 10:00 |
Last Modified: | 08 Sep 2022 10:00 |
Status: | Published |
Publisher: | Association for Computational Linguistics |
Refereed: | Yes |
Identification Number: | 10.18653/v1/P17-2003 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:190609 |