Abstract
Argumentation schemes are patterns of human reasoning which have been detailed extensively in philosophy and psychology. In this paper we demonstrate that the structure of such schemes can provide rich information to the task of automatically identify complex argumentative structures in natural language text. By training a range of classifiers to identify the individual proposition types which occur in these schemes, it is possible not only to determine where a scheme is being used, but also the roles played by its component parts. Furthermore, this task can be performed on segmented natural language, with no prior knowledge of the text’s argumentative structure.
Original language | English |
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Title of host publication | Computational Models of Argument |
Subtitle of host publication | Proceedings from the Sixth International Conference on Computational Models of Argument (COMMA) |
Editors | Pietro Baroni, Thomas F. Gordon, Tatjana Scheffler, Manfred Stede |
Place of Publication | Netherlands |
Publisher | IOS Press |
Pages | 379-390 |
Number of pages | 12 |
Volume | 287 |
ISBN (Electronic) | 9781614996866 |
ISBN (Print) | 9781614996859 |
DOIs | |
Publication status | Published - 2016 |
Event | The 6th International Conference on Computational Models of Argument - University of Potsdam, Potsdam, Germany Duration: 13 Sept 2016 → 16 Sept 2016 http://www.ling.uni-potsdam.de/comma2016/ |
Publication series
Name | Frontiers in Artificial Intelligence and Applications |
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Publisher | IOS Press |
Volume | 287 |
ISSN (Print) | 0922-6389 |
ISSN (Electronic) | 1879-8314 |
Conference
Conference | The 6th International Conference on Computational Models of Argument |
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Country/Territory | Germany |
City | Potsdam |
Period | 13/09/16 → 16/09/16 |
Internet address |
Keywords
- Argumentation Schemes
- Argument Mining
- Natural Language Processing