Coreference Resolution for Structured Drug Product Labels

Halil Kilicoglu, Dina Demner-Fushman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

FDA drug package inserts provide comprehensive and authoritative information about drugs. DailyMed database is a repository of structured product labels extracted from these package inserts. Most salient information about drugs remains in free text portions of these labels. Extracting information from these portions can improve the safety and quality of drug prescription. In this paper, we present a study that focuses on resolution of coreferential information from drug labels contained in DailyMed. We generalized and expanded an existing rule-based coreference resolution module for this purpose. Enhancements include resolution of set/instance anaphora, recognition of appositive constructions and wider use of UMLS semantic knowledge. We obtained an improvement of 40% over the baseline with unweighted average F1-measure using B-CUBED, MUC, and CEAF metrics. The results underscore the importance of set/instance anaphora and appositive constructions in this type of text and point out the shortcomings in coreference annotation in the dataset.

Original languageEnglish (US)
Title of host publicationACL 2014 - BioNLP 2014, Workshop on Biomedical Natural Language Processing, Proceedings of the Workshop
PublisherAssociation for Computational Linguistics (ACL)
Pages45-53
Number of pages9
ISBN (Electronic)9781941643181
StatePublished - 2014
Externally publishedYes
EventACL 2014 Workshop on Biomedical Natural Language Processing, BioNLP 2014 - Baltimore, United States
Duration: Jun 27 2014Jun 28 2014

Publication series

NameProceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN (Print)0736-587X

Conference

ConferenceACL 2014 Workshop on Biomedical Natural Language Processing, BioNLP 2014
Country/TerritoryUnited States
CityBaltimore
Period6/27/146/28/14

ASJC Scopus subject areas

  • Computer Science Applications
  • Linguistics and Language
  • Language and Linguistics

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