A study to improve the efficiency of a discourse parsing system

Authors:
Huong T. Le;Geetha Abeysinghe
Affiliations:
School of Computing Science, Middlesex University, The Burroughs, London, UK;School of Computing Science, Middlesex University, The Burroughs, London, UK
Venue:
CICLing'03 Proceedings of the 4th international conference on Computational linguistics and intelligent text processing
Year:
2003

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Abstract

This paper presents a study of the implementation of a discourse parsing system, where only significant features are considered. Rhetorical relations are recognized based on three types of cue phrases (the normal cue phrases, Noun-Phrase cues and Verb-Phrase cues), and different textual coherence devices. The parsing algorithm and its rule set are developed in order to create a system with high accuracy and low complexity. The data used in this system are taken from the RST Discourse Treebank of the Linguistic Data Consortium (LDC).