Stab, Christian ; Gurevych, Iryna (2017)
Parsing Argumentation Structures in Persuasive Essays.
In: Computational Linguistics, 43 (3)
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
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.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2017 |
| Autor(en): | Stab, Christian ; Gurevych, Iryna |
| Art des Eintrags: | Bibliographie |
| Titel: | Parsing Argumentation Structures in Persuasive Essays |
| Sprache: | Englisch |
| Publikationsjahr: | September 2017 |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Computational Linguistics |
| Jahrgang/Volume einer Zeitschrift: | 43 |
| (Heft-)Nummer: | 3 |
| URL / URN: | https://www.mitpressjournals.org/doi/pdf/10.1162/COLI_a_0029... |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | 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. |
| Freie Schlagworte: | UKP_a_ArMin |
| ID-Nummer: | TUD-CS-2016-0087 |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung DFG-Graduiertenkollegs DFG-Graduiertenkollegs > Graduiertenkolleg 1994 Adaptive Informationsaufbereitung aus heterogenen Quellen |
| Hinterlegungsdatum: | 31 Dez 2016 14:29 |
| Letzte Änderung: | 24 Jan 2020 12:03 |
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