A Benchmark Dataset for Automatic Detection of Claims and Evidence in the Context of Controversial Topics

Ehud Aharoni, Anatoly Polnarov, Tamar Lavee, Daniel Hershcovich, Ran Levy, Ruty Rinott, Dan Gutfreund, Noam Slonim


Anthology ID:
W14-2109
Volume:
Proceedings of the First Workshop on Argumentation Mining
Month:
June
Year:
2014
Address:
Baltimore, Maryland
Editors:
Nancy Green, Kevin Ashley, Diane Litman, Chris Reed, Vern Walker
Venue:
WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
64–68
Language:
URL:
https://aclanthology.org/W14-2109
DOI:
10.3115/v1/W14-2109
Bibkey:
Cite (ACL):
Ehud Aharoni, Anatoly Polnarov, Tamar Lavee, Daniel Hershcovich, Ran Levy, Ruty Rinott, Dan Gutfreund, and Noam Slonim. 2014. A Benchmark Dataset for Automatic Detection of Claims and Evidence in the Context of Controversial Topics. In Proceedings of the First Workshop on Argumentation Mining, pages 64–68, Baltimore, Maryland. Association for Computational Linguistics.
Cite (Informal):
A Benchmark Dataset for Automatic Detection of Claims and Evidence in the Context of Controversial Topics (Aharoni et al., 2014)
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PDF:
https://aclanthology.org/W14-2109.pdf