Title

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

Source of Publication

International Journal of Intelligent Systems Technologies and Applications

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%.

Document Type

Article

First Page

281

Last Page

302

Publication Date

1-1-2019

DOI

10.1504/IJISTA.2019.099345

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