Neural End-to-End Learning for Computational Argumentation Mining

We investigate neural techniques for end-to-end computational argumentation mining (AM). We frame AM both as a token-based dependency parsing and as a token-based sequence tagging problem, including a multi-task learning setup. Contrary to models that operate on the argument component level, we find...

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Bibliographische Detailangaben

Hauptverfasser:	Eger, Steffen, Daxenberger, Johannes, Gurevych, Iryna
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computation and Language
Online-Zugang:	Volltext bestellen
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