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Knowledge-Driven Argument Mining Based on the Qualia Structure

Saint-Dizier, Patrick Knowledge-Driven Argument Mining Based on the Qualia Structure. (2017) Argument and Computation, 8 (2). 193-210. ISSN 1946-2166

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Official URL: https://doi.org/10.3233/AAC-170124

Abstract

Given a controversial issue, argument mining from texts in natural language is extremely challenging: besides linguistic aspects, domain knowledge is often required together with appropriate forms of inferences to identify arguments. Via the analysis of various corpora, this contribution explores the types of knowledge that are required to develop an efficient argument mining system. We show that the Qualia structure of the Generative Lexicon with some extensions and a specific interpretation has some expressive capabilities which are appropriate for this task.

Item Type:Article
Additional Information:This article is published online with Open Access and distributed under the terms of the Creative Commons Attribution Non-Commercial License (CC BY-NC 4.0).
HAL Id:hal-02535069
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
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Deposited On:07 Apr 2020 10:54

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