Article

End-to-end coreference resolution for clinical narratives

Authors:

Prateek Jindal,

Dan RothAuthors Info & Claims

IJCAI '13: Proceedings of the Twenty-Third international joint conference on Artificial Intelligence

Pages 2106 - 2112

Published: 03 August 2013 Publication History

Abstract

Coreference resolution is the problem of clustering mentions into entities and is very critical for natural language understanding. This paper studies the problem of coreference resolution in the context of the important domain of clinical text. Clinical text is unique because it requires significant use of domain knowledge to support coreference resolution. It also has specific discourse characteristics which impose several constraints on coreference decisions. We present a principled framework to incorporate knowledge-based constraints in the coreference model. We also show that different pronouns behave quite differently, necessitating the development of distinct ways for resolving different pronouns. Our methods result in significant performance improvements and we report the best results on a clinical corpora that has been used in coreference shared tasks. Moreover, for the first time, we report the results for end-to-end coreference resolution on this corpora.

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Cited By

Jindal PGunter CRoth DBaldi PWang W(2014)Detecting privacy-sensitive events in medical textProceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics10.1145/2649387.2662451(617-620)Online publication date: 20-Sep-2014
https://dl.acm.org/doi/10.1145/2649387.2662451
Jindal PRoth DGunter CBaldi PWang W(2014)Joint inference for end-to-end coreference resolution for clinical notesProceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics10.1145/2649387.2649437(192-201)Online publication date: 20-Sep-2014
https://dl.acm.org/doi/10.1145/2649387.2649437
Mukherjee SWeikum GDanescu-Niculescu-Mizil CMacskassy SPerlich CLeskovec JWang WGhani R(2014)People on drugsProceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining10.1145/2623330.2623714(65-74)Online publication date: 24-Aug-2014
https://dl.acm.org/doi/10.1145/2623330.2623714

End-to-end coreference resolution for clinical narratives
1. Hardware
  1. Power and energy
    1. Power estimation and optimization

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cover image Guide Proceedings

IJCAI '13: Proceedings of the Twenty-Third international joint conference on Artificial Intelligence

August 2013

3266 pages

ISBN:9781577356332

Editor:
Francesca Rossi
University of Padova

Sponsors

The International Joint Conferences on Artificial Intelligence, Inc. (IJCAI)

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AAAI Press

Publication History

Published: 03 August 2013

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Cited By

Jindal PGunter CRoth DBaldi PWang W(2014)Detecting privacy-sensitive events in medical textProceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics10.1145/2649387.2662451(617-620)Online publication date: 20-Sep-2014
https://dl.acm.org/doi/10.1145/2649387.2662451
Jindal PRoth DGunter CBaldi PWang W(2014)Joint inference for end-to-end coreference resolution for clinical notesProceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics10.1145/2649387.2649437(192-201)Online publication date: 20-Sep-2014
https://dl.acm.org/doi/10.1145/2649387.2649437
Mukherjee SWeikum GDanescu-Niculescu-Mizil CMacskassy SPerlich CLeskovec JWang WGhani R(2014)People on drugsProceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining10.1145/2623330.2623714(65-74)Online publication date: 24-Aug-2014
https://dl.acm.org/doi/10.1145/2623330.2623714

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