Journal
COMPUTATIONAL LINGUISTICS
Volume 43, Issue 3, Pages 619-659Publisher
MIT PRESS
DOI: 10.1162/COLI_a_00295
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Funding
- Volkswagen Foundation as part of the Lichtenberg-Professorship Program [I/82806]
- German Federal Ministry of Education and Research (BMBF) as a part of the Software Campus project AWS [01-S12054]
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In this article, we present a novel approach for parsing argumentation structures. We identify argument components using sequence labeling at the token level and apply a new joint model for detecting argumentation structures. The proposed model globally optimizes argument component types and argumentative relations using Integer Linear Programming. We show that our model significantly outperforms challenging heuristic baselines on two different types of discourse. Moreover, we introduce a novel corpus of persuasive essays annotated with argumentation structures. We show that our annotation scheme and annotation guidelines successfully guide human annotators to substantial agreement.
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