Argumentative classification of extracted sentences as a first step towards flexible abstracting
From HLT@INESC-ID
Bibliographical data
- Source: Advances in Automatic Text Summarization
- Pages: 155-171
- Year: 1999
- Authors: Simone Teufel and Marc Moens
- Publisher: MIT Press
Abstract
Knowledge about the rhetorical structure of a text is useful for automatic abstraction. We are interested in the automatic extraction of rhetorical units from the source text, units such as PROBLEM STATEMENT, CON-CLUSIONS alld RESULTS. We want to use such extracts to generate high-compression abstracts of scientific articles. In this paper, we present an extension of Kupiec, Pealersen and Chen's (1995) methodology for trainable statistical sentence extraction. Our extension addition-ally classifies the extracted sentences according to their rhetorical role.