Mining and Visualizing the Narration Tree of Hadiths (Prophetic Traditions)

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Author(s): Aqil Azmi (King Saud University, Saudi Arabia)and Nawaf AlBadia (General Organization for Social Insurance, Saudi Arabia)
Copyright: 2012
Pages: 19
Source title: Cross-Disciplinary Advances in Applied Natural Language Processing: Issues and Approaches
Source Author(s)/Editor(s): Chutima Boonthum-Denecke (Hampton University, USA), Philip M. McCarthy (The University of Memphis, USA)and Travis Lamkin (University of Memphis, USA)
DOI: 10.4018/978-1-61350-447-5.ch016

Keywords: Artificial Intelligence / Computational Linguistics / Computer Science & IT / Information Science Reference

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Abstract

Hadiths are narrations originating from the words and deeds of Prophet Muhammad. Each hadith starts with a list of narrators involved in transmitting it. A hadith scholar judges a hadith based on the narration chain along with the individual narrators in the chain. In this chapter, the authors report on a method that automatically extracts the transmission chains from the hadith text and graphically display it. Computationally, this is a challenging problem. Foremost each hadith has its own peculiar way of listing narrators; and the text of hadith is in Arabic, a language rich in morphology. The proposed solution involves parsing and annotating the hadith text and recognizing the narrators’ names. The authors use shallow parsing along with a domain specific grammar to parse the hadith content. Experiments on sample hadiths show our approach to have a very good success rate.

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