Using Question-Answering Techniques to Implement a Knowledge-Driven Argument Mining Approach

Patrick Saint-Dizier


Abstract
This short paper presents a first implementation of a knowledge-driven argument mining approach. The major processing steps and language resources of the system are surveyed. An indicative evaluation outlines challenges and improvement directions.
Anthology ID:
W17-5111
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:
85–90
Language:
URL:
https://preview.aclanthology.org/build-pipeline-with-new-library/W17-5111/
DOI:
10.18653/v1/W17-5111
Bibkey:
Cite (ACL):
Patrick Saint-Dizier. 2017. Using Question-Answering Techniques to Implement a Knowledge-Driven Argument Mining Approach. In Proceedings of the 4th Workshop on Argument Mining, pages 85–90, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
Using Question-Answering Techniques to Implement a Knowledge-Driven Argument Mining Approach (Saint-Dizier, ArgMining 2017)
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PDF:
https://preview.aclanthology.org/build-pipeline-with-new-library/W17-5111.pdf