Acquiring Predicate Paraphrases from News Tweets

Vered Shwartz, Gabriel Stanovsky, Ido Dagan


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.
Anthology ID:
S17-1019
Volume:
Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)
Month:
August
Year:
2017
Address:
Vancouver, Canada
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
155–160
Language:
URL:
https://www.aclweb.org/anthology/S17-1019
DOI:
10.18653/v1/S17-1019
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S17-1019.pdf