Automatic identification of rhetorical relations among intra-sentence discourse segments in Arabic

Document Type

Article

Source of Publication

International Journal of Intelligent Systems Technologies and Applications

Publication Date

1-1-2019

Abstract

© 2019 Inderscience Enterprises Ltd. Identifying discourse relations, whether implicit or explicit, has seen renewed interest and remains an open challenge. We present the first model that automatically identifies both explicit and implicit rhetorical relations among intra-sentence discourse segments in Arabic text. We build a large discourse annotated corpora following the rhetorical structure theory framework. Our list of rhetorical relations is organised into three level hierarchies of 23 fine-grained relations, grouped into seven classes. To automatically learn these relations, we evaluate and reuse features from literature, and contribute three additional features: accusative of purpose, specific connectives and the number of antonym words. We perform experiments on identifying fine-grained and coarse-grained relations. The results show that compared with all the baselines, our model achieves the best performance in most cases, with an accuracy of 91.05%.

ISSN

1740-8865

Publisher

Inderscience Publishers

Volume

18

Issue

3

First Page

281

Last Page

302

Disciplines

Computer Sciences

Keywords

Arabic language, Discourse relations, Rhetorical structure theory

Scopus ID

85065124253

Indexed in Scopus

yes

Open Access

no

Link to Full Text

Share

COinS