Moosavi, N.S. orcid.org/0000-0002-8332-307X, Born, L., Poesio, M. et al. (1 more author) (2019) Using automatically extracted minimum spans to disentangle coreference evaluation from boundary detection. In: Korhonen, A., Traum, D. and Màrquez, L., (eds.) Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019). 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019), 28 Jul - 02 Aug 2019, Florence, Italy. Association for Computational Linguistics , pp. 4168-4178. ISBN 9781950737482
Abstract
The common practice in coreference resolution is to identify and evaluate the maximum span of mentions. The use of maximum spans tangles coreference evaluation with the challenges of mention boundary detection like prepositional phrase attachment. To address this problem, minimum spans are manually annotated in smaller corpora. However, this additional annotation is costly and therefore, this solution does not scale to large corpora. In this paper, we propose the MINA algorithm for automatically extracting minimum spans to benefit from minimum span evaluation in all corpora. We show that the extracted minimum spans by MINA are consistent with those that are manually annotated by experts. Our experiments show that using minimum spans is in particular important in cross-dataset coreference evaluation, in which detected mention boundaries are noisier due to domain shift. We have integrated MINA into https://github.com/ns-moosavi/coval for reporting standard coreference scores based on both maximum and automatically detected minimum spans.
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: | © 2019 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: | 07 Sep 2022 11:44 |
Last Modified: | 07 Sep 2022 14:24 |
Status: | Published |
Publisher: | Association for Computational Linguistics |
Refereed: | Yes |
Identification Number: | 10.18653/v1/P19-1408 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:190599 |