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://preview.aclanthology.org/build-pipeline-with-new-library/W14-2109/
- DOI:
- 10.3115/v1/W14-2109
- 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)
- PDF:
- https://preview.aclanthology.org/build-pipeline-with-new-library/W14-2109.pdf