Computational Argumentation Synthesis as a Language Modeling Task

verfasst von

Roxanne El Baff, Henning Wachsmuth, Khalid Al-Khatib, Manfred Stede, Benno Stein

Abstract

Synthesis approaches in computational argumentation so far are restricted to generating claim-like argument units or short summaries of debates. Ultimately, however, we expect computers to generate whole new arguments for a given stance towards some topic, backing up claims following argumentative and rhetorical considerations. In this paper, we approach such an argumentation synthesis as a language modeling task. In our language model, argumentative discourse units are the “words”, and arguments represent the “sentences”. Given a pool of units for any unseen topic-stance pair, the model selects a set of unit types according to a basic rhetorical strategy (logos vs. pathos), arranges the structure of the types based on the units’ argumentative roles, and finally “phrases” an argument by instantiating the structure with semantically coherent units from the pool. Our evaluation suggests that the model can, to some extent, mimic the human synthesis of strategy-specific arguments.

Externe Organisation(en)

Bauhaus-Universität Weimar
Universität Paderborn
Universität Potsdam

Typ

Aufsatz in Konferenzband

Seiten

54-64

Anzahl der Seiten

11

Publikationsdatum

2019

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Software

Elektronische Version(en)

https://doi.org/10.18653/v1/W19-8607 (Zugang: Offen)