TU Darmstadt / ULB / TUbiblio

The Argument Reasoning Comprehension Task: Identification and Reconstruction of Implicit Warrants

Habernal, Ivan ; Wachsmuth, Henning ; Gurevych, Iryna ; Stein, Benno (2018)
The Argument Reasoning Comprehension Task: Identification and Reconstruction of Implicit Warrants.
New Orleans, USA
Konferenzveröffentlichung, Bibliographie

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2018
Autor(en): Habernal, Ivan ; Wachsmuth, Henning ; Gurevych, Iryna ; Stein, Benno
Art des Eintrags: Bibliographie
Titel: The Argument Reasoning Comprehension Task: Identification and Reconstruction of Implicit Warrants
Sprache: Englisch
Publikationsjahr: Juni 2018
Verlag: Association for Computational Linguistics
Buchtitel: Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Veranstaltungsort: New Orleans, USA
URL / URN: http://aclweb.org/anthology/N18-1175
Zugehörige Links:
Freie Schlagworte: UKP_a_ArMin;UKP_p_ArguAna
ID-Nummer: TUD-CS-2018-0029
Zusätzliche Informationen:

Reasoning is a crucial part of natural language argumentation. To comprehend an argument, one must analyze its warrant, which explains why its claim follows from its premises. As arguments are highly contextualized, warrants are usually presupposed and left implicit. Thus, the comprehension does not only require language understanding and logic skills, but also depends on common sense. In this paper we develop a methodology for reconstructing warrants systematically. We operationalize it in a scalable crowdsourcing process, resulting in a freely licensed dataset with warrants for 2k authentic arguments from news comments. On this basis, we present a new challenging task, the argument reasoning comprehension task. Given an argument with a claim and a premise, the goal is to choose the correct implicit warrant from two options. Both warrants are plausible and lexically close, but lead to contradicting claims. A solution to this task will define a substantial step towards automatic warrant reconstruction. However, experiments with several neural attention and language models reveal that current approaches do not suffice.

Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung
DFG-Graduiertenkollegs
DFG-Graduiertenkollegs > Graduiertenkolleg 1994 Adaptive Informationsaufbereitung aus heterogenen Quellen
Hinterlegungsdatum: 16 Feb 2018 08:51
Letzte Änderung: 24 Jan 2020 12:03
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