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        <title>Acquiring Predicate Paraphrases from News Tweets</title>
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    <abstract>We present a simple method for ever-growing 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.</abstract>
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%0 Conference Proceedings
%T Acquiring Predicate Paraphrases from News Tweets
%A Shwartz, Vered
%A Stanovsky, Gabriel
%A Dagan, Ido
%Y Ide, Nancy
%Y Herbelot, Aurélie
%Y Màrquez, Lluís
%S Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada
%F shwartz-etal-2017-acquiring
%X We present a simple method for ever-growing 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.
%R 10.18653/v1/S17-1019
%U https://aclanthology.org/S17-1019
%U https://doi.org/10.18653/v1/S17-1019
%P 155-160

Markdown (Informal)

[Acquiring Predicate Paraphrases from News Tweets](https://aclanthology.org/S17-1019) (Shwartz et al., *SEM 2017)

• Acquiring Predicate Paraphrases from News Tweets (Shwartz et al., *SEM 2017)

ACL

• Vered Shwartz, Gabriel Stanovsky, and Ido Dagan. 2017. Acquiring Predicate Paraphrases from News Tweets. In Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017), pages 155–160, Vancouver, Canada. Association for Computational Linguistics.