Surawat Pothong
2024
Flee the Flaw: Annotating the Underlying Logic of Fallacious Arguments Through Templates and Slot-filling
Irfan Robbani
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Paul Reisert
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Surawat Pothong
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Naoya Inoue
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Camélia Guerraoui
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Wenzhi Wang
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Shoichi Naito
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Jungmin Choi
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Kentaro Inui
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Prior research in computational argumentation has mainly focused on scoring the quality of arguments, with less attention on explicating logical errors. In this work, we introduce four sets of explainable templates for common informal logical fallacies designed to explicate a fallacy’s implicit logic. Using our templates, we conduct an annotation study on top of 400 fallacious arguments taken from LOGIC dataset and achieve a high agreement score (Krippendorf’s 𝛼 of 0.54) and reasonable coverage 83%. Finally, we conduct an experiment for detecting the structure of fallacies and discover that state-of-the-art language models struggle with detecting fallacy templates (0.47 accuracy). To facilitate research on fallacies, we make our dataset and guidelines publicly available.
Designing Logic Pattern Templates for Counter-Argument Logical Structure Analysis
Shoichi Naito
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Wenzhi Wang
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Paul Reisert
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Naoya Inoue
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Camélia Guerraoui
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Kenshi Yamaguchi
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Jungmin Choi
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Irfan Robbani
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Surawat Pothong
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Kentaro Inui
Findings of the Association for Computational Linguistics: EMNLP 2024
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Co-authors
- Irfan Robbani 2
- Paul Reisert 2
- Naoya Inoue 2
- Camélia Guerraoui 2
- Wenzhi Wang 2
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