Bayesian Argumentation-Scheme Networks: A Probabilistic Model of Argument Validity Facilitated by Argumentation Schemes

Takahiro Kondo, Koki Washio, Katsuhiko Hayashi, Yusuke Miyao


Abstract
We propose a methodology for representing the reasoning structure of arguments using Bayesian networks and predicate logic facilitated by argumentation schemes. We express the meaning of text segments using predicate logic and map the boolean values of predicate logic expressions to nodes in a Bayesian network. The reasoning structure among text segments is described with a directed acyclic graph. While our formalism is highly expressive and capable of describing the informal logic of human arguments, it is too open-ended to actually build a network for an argument. It is not at all obvious which segment of argumentative text should be considered as a node in a Bayesian network, and how to decide the dependencies among nodes. To alleviate the difficulty, we provide abstract network fragments, called idioms, which represent typical argument justification patterns derived from argumentation schemes. The network construction process is decomposed into idiom selection, idiom instantiation, and idiom combination. We define 17 idioms in total by referring to argumentation schemes as well as analyzing actual arguments and fitting idioms to them. We also create a dataset consisting of pairs of an argumentative text and a corresponding Bayesian network. Our dataset contains about 2,400 pairs, which is large in the research area of argumentation schemes.
Anthology ID:
2021.argmining-1.11
Volume:
Proceedings of the 8th Workshop on Argument Mining
Month:
November
Year:
2021
Address:
Punta Cana, Dominican Republic
Venues:
ArgMining | EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
112–124
Language:
URL:
https://aclanthology.org/2021.argmining-1.11
DOI:
10.18653/v1/2021.argmining-1.11
Bibkey:
Cite (ACL):
Takahiro Kondo, Koki Washio, Katsuhiko Hayashi, and Yusuke Miyao. 2021. Bayesian Argumentation-Scheme Networks: A Probabilistic Model of Argument Validity Facilitated by Argumentation Schemes. In Proceedings of the 8th Workshop on Argument Mining, pages 112–124, Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Bayesian Argumentation-Scheme Networks: A Probabilistic Model of Argument Validity Facilitated by Argumentation Schemes (Kondo et al., ArgMining 2021)
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PDF:
https://aclanthology.org/2021.argmining-1.11.pdf