Abstract

The two fundamental sources of Islamic legislation are Qur'an and the Hadith. The Hadiths, or Prophetic Traditions, are narrations originating from the sayings and conducts of Prophet Muhammad. Each Hadith starts with a list of narrators involved in transmitting it followed by the transmitted text. The Hadith corpus is extremely huge and runs into hundreds of volumes. Due to its legislative importance, Hadiths have been carefully scrutinized by hadith scholars. One way a scholar may grade a Hadith is by its narration chain and the individual narrators in the chain. In this paper we report on a system that automatically generates the transmission chains of a Hadith and graphically display it. Computationally, this is a challenging problem. The text of Hadith is in Arabic, a morphologically rich language; and each Hadith has its own peculiar way of listing narrators. Our solution involves parsing and annotating the Hadith text and identifying the narrators' names. We 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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