Acquiring predicate paraphrases from news tweets

Vered Shwartz, Gabriel Stanovsky, Ido Dagan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

We present a simple method for evergrowing extraction of predicate paraphrases from news headlines in Twitter. Analysis of the output of ten weeks of collection shows that the accuracy of paraphrases with different support levels is estimated between 60-86%. We also demonstrate that our resource is to a large extent complementary to existing resources, providing many novel paraphrases. Our resource is publicly available, continuously expanding based on daily news.

Original languageAmerican English
Title of host publication*SEM 2017 - 6th Joint Conference on Lexical and Computational Semantics, Proceedings
PublisherAssociation for Computational Linguistics (ACL)
Pages155-160
Number of pages6
ISBN (Electronic)9781945626531
DOIs
StatePublished - 2017
Externally publishedYes
Event6th Joint Conference on Lexical and Computational Semantics, *SEM 2017 - Vancouver, Canada
Duration: 3 Aug 20174 Aug 2017

Publication series

Name*SEM 2017 - 6th Joint Conference on Lexical and Computational Semantics, Proceedings

Conference

Conference6th Joint Conference on Lexical and Computational Semantics, *SEM 2017
Country/TerritoryCanada
CityVancouver
Period3/08/174/08/17

Bibliographical note

Publisher Copyright:
© 2017 Association for Computational Linguistics.

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