Discourse segmentation for Spanish based on shallow parsing

Authors:
Iria Da Cunha;Eric SanJuan;Juan-Manuel Torres-Moreno;Marina Lloberes;Irene Castellón
Affiliations:
Institute for Applied Linguistics, UPF, Barcelona, Spain and Laboratoire Informatique d'Avignon, Avignon Cedex 9, France and Instituto de Ingeniería, UNAM, Mexico;Laboratoire Informatique d'Avignon, Avignon Cedex 9, France;Laboratoire Informatique d'Avignon, Avignon Cedex 9, France and École Polytechnique de Montréal, DGI, Montréal, Québec, Canada;GRIAL, Universitat de Barcelona, Barcelona, Spain;GRIAL, Universitat de Barcelona, Barcelona, Spain
Venue:
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
Year:
2010

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Abstract

Nowadays discourse parsing is a very prominent research topic. However, there is not a discourse parser for Spanish texts. The first stage in order to develop this tool is discourse segmentation. In this work, we present DiSeg, the first discourse segmenter for Spanish, which uses the framework of Rhetorical Structure Theory and is based on lexical and syntactic rules. We describe the system and we evaluate its performance against a gold standard corpus, obtaining promising results.