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Discourse-Driven Argument Mining in Scientific Abstracts - 2019

Discourse-Driven Argument Mining In Scientific Abstracts

Research Area:  Machine Learning

Abstract:

Argument mining consists in the automatic identification of argumentative structures in texts. In this work we address the open question of whether discourse-level annotations can contribute to facilitate the identification of argumentative components and relations in scientific literature. We conduct a pilot study by enriching a corpus of computational linguistics abstracts that contains discourse annotations with a new argumentative annotation level. The results obtained from preliminary experiments confirm the potential value of the proposed approach.

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Author(s) Name:  Pablo Accuosto, Horacio Saggion

Journal name:  Computer Science

Conferrence name:  

Publisher name:  Springer

DOI:  10.1007/978-3-030-23281-8_15

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