DiSeg 1.0: The first system for Spanish discourse segmentation

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, divided in a medical and a terminological subcorpus. We obtain promising results, which means that discourse segmentation is possible using shallow parsing.

► We present DiSeg, the first system for Spanish discourse segmentation. ► The system is based on the syntactic shallow parser Freeling. ► We provide a gold standard including Spanish texts from medical and linguistic domains. ► We evaluate the system obtaining good results. ► We will go on working to develop the first Spanish discourse parser.