Abstract
This paper describes a pilot study to evaluate human analysts’ ability to identify the argumentation scheme and premises of an argument having an implicit conclusion. In preparation for the study, argumentation scheme definitions were crafted for genetics research articles. The schemes were defined in semantic terms, following a proposal to use semantic rules to mine arguments in that literature.- Anthology ID:
- W17-5109
- Volume:
- Proceedings of the 4th Workshop on Argument Mining
- Month:
- September
- Year:
- 2017
- Address:
- Copenhagen, Denmark
- Editors:
- Ivan Habernal, Iryna Gurevych, Kevin Ashley, Claire Cardie, Nancy Green, Diane Litman, Georgios Petasis, Chris Reed, Noam Slonim, Vern Walker
- Venue:
- ArgMining
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 73–78
- Language:
- URL:
- https://aclanthology.org/W17-5109
- DOI:
- 10.18653/v1/W17-5109
- Cite (ACL):
- Nancy Green. 2017. Manual Identification of Arguments with Implicit Conclusions Using Semantic Rules for Argument Mining. In Proceedings of the 4th Workshop on Argument Mining, pages 73–78, Copenhagen, Denmark. Association for Computational Linguistics.
- Cite (Informal):
- Manual Identification of Arguments with Implicit Conclusions Using Semantic Rules for Argument Mining (Green, ArgMining 2017)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/W17-5109.pdf