An information extraction customizer

Ralph Grishman, Yifan He

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

Abstract

When an information extraction system is applied to a new task or domain, we must specify the classes of entities and relations to be extracted. This is best done by a subject matter expert, who may have little training in NLP. To meet this need, we have developed a toolset which is able to analyze a corpus and aid the user in building the specifications of the entity and relation types.

Original languageEnglish (US)
Title of host publicationText, Speech, and Dialogue - 17th International Conference, TSD 2014, Proceedings
PublisherSpringer Verlag
Pages3-10
Number of pages8
ISBN (Print)9783319108155
DOIs
StatePublished - 2014
Event17th International Conference on Text, Speech, and Dialogue, TSD 2014 - Brno, Czech Republic
Duration: Sep 8 2014Sep 12 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8655 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other17th International Conference on Text, Speech, and Dialogue, TSD 2014
CountryCzech Republic
CityBrno
Period9/8/149/12/14

Keywords

  • distributional analysis
  • information extraction

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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