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Corpus-based identification of non-anaphoric noun phrases

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ACL '99: Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics

Pages 373 - 380

https://doi.org/10.3115/1034678.1034737

Published: 20 June 1999 Publication History

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Abstract

Coreference resolution involves finding antecedents for anaphoric discourse entities, such as definite noun phrases. But many definite noun phrases are not anaphoric because their meaning can be understood from general world knowledge (e.g., "the White House" or "the news media"). We have developed a corpus-based algorithm for automatically identifying definite noun phrases that are non-anaphoric, which has the potential to improve the efficiency and accuracy of coreference resolution systems. Our algorithm generates lists of non-anaphoric noun phrases and noun phrase patterns from a training corpus and uses them to recognize non-anaphoric noun phrases in new texts. Using 1600 MUC-4 terrorism news articles as the training corpus, our approach achieved 78% recall and 87% precision at identifying such noun phrases in 50 text documents.

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Cited By

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Cahill ARiester ALee GGinzburg J(2012)Automatically acquiring fine-grained information status distinctions in GermanProceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue10.5555/2392800.2392842(232-236)Online publication date: 5-Jul-2012
https://dl.acm.org/doi/10.5555/2392800.2392842
Rahman ANg VMerlo PBarzilay RJohnson M(2011)Learning the information status of noun phrases in spoken dialoguesProceedings of the Conference on Empirical Methods in Natural Language Processing10.5555/2145432.2145547(1069-1080)Online publication date: 27-Jul-2011
https://dl.acm.org/doi/10.5555/2145432.2145547
Zheng JChapman WCrowley RSavova G(2011)Methodological ReviewJournal of Biomedical Informatics10.1016/j.jbi.2011.08.00644:6(1113-1122)Online publication date: 1-Dec-2011
https://dl.acm.org/doi/10.1016/j.jbi.2011.08.006
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Corpus-based identification of non-anaphoric noun phrases
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Published In

ACL '99: Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics

June 1999

642 pages

ISBN:1558606093

Program Chairs:
Robert Dale,
Ken Church

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Association for Computational Linguistics

United States

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Published: 20 June 1999

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Overall Acceptance Rate 85 of 443 submissions, 19%

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Cahill ARiester ALee GGinzburg J(2012)Automatically acquiring fine-grained information status distinctions in GermanProceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue10.5555/2392800.2392842(232-236)Online publication date: 5-Jul-2012
https://dl.acm.org/doi/10.5555/2392800.2392842
Rahman ANg VMerlo PBarzilay RJohnson M(2011)Learning the information status of noun phrases in spoken dialoguesProceedings of the Conference on Empirical Methods in Natural Language Processing10.5555/2145432.2145547(1069-1080)Online publication date: 27-Jul-2011
https://dl.acm.org/doi/10.5555/2145432.2145547
Zheng JChapman WCrowley RSavova G(2011)Methodological ReviewJournal of Biomedical Informatics10.1016/j.jbi.2011.08.00644:6(1113-1122)Online publication date: 1-Dec-2011
https://dl.acm.org/doi/10.1016/j.jbi.2011.08.006
Kong FZhou GQian LZhu QJoshi AHuang CJurafsky D(2010)Dependency-driven anaphoricity determination for coreference resolutionProceedings of the 23rd International Conference on Computational Linguistics10.5555/1873781.1873849(599-607)Online publication date: 23-Aug-2010
https://dl.acm.org/doi/10.5555/1873781.1873849
Ng VHajič J(2010)Supervised noun phrase coreference researchProceedings of the 48th Annual Meeting of the Association for Computational Linguistics10.5555/1858681.1858823(1396-1411)Online publication date: 11-Jul-2010
https://dl.acm.org/doi/10.5555/1858681.1858823
Zhou GKong FKoehn PMihalcea R(2009)Global learning of noun phrase anaphoricity in coreference resolution via label propagationProceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 210.5555/1699571.1699640(978-986)Online publication date: 6-Aug-2009
https://dl.acm.org/doi/10.5555/1699571.1699640
Rahman ANg VKoehn PMihalcea R(2009)Supervised models for coreference resolutionProceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 210.5555/1699571.1699639(968-977)Online publication date: 6-Aug-2009
https://dl.acm.org/doi/10.5555/1699571.1699639
Ng VOstendorf MCollins MNarayanan SOard D(2009)Graph-cut-based anaphoricity determination for coreference resolutionProceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics10.5555/1620754.1620838(575-583)Online publication date: 31-May-2009
https://dl.acm.org/doi/10.5555/1620754.1620838
Recasens MDemberg VMa YReiter N(2009)A chain-starting classifier of definite NPs in SpanishProceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop10.5555/1609179.1609185(46-53)Online publication date: 2-Apr-2009
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Elsner MCharniak E(2008)Coreference-inspired coherence modelingProceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers10.5555/1557690.1557702(41-44)Online publication date: 16-Jun-2008
https://dl.acm.org/doi/10.5555/1557690.1557702
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An estimate of referent of noun phrases in Japanese sentences

Identifying anaphoric and non-anaphoric noun phrases to improve coreference resolution

Identification of Maximal-Length Noun Phrases Based on Maximal-Length Preposition Phrases in Chinese

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