A Novel LLM-Based Approach for Automated Seerah-Hadith Mapping: Connecting Islamic Historical Narratives Through Vector Search and Semantic Analysis
Mushfiqur Rahman Talha · Mohammad Shams · Riasat Islam · Nabil Mosharraf
Abstract
Seerah and Hadith are essential sources of Islamic knowledge, but there has been limited research on systematically linking these two areas. This paper introduces the "Seerah-Hadith Mapping" project, which uses Large Language Models (LLMs) to map related passages between Seerah and Hadith. By adding new connections between these texts, this approach builds on existing scholarship and helps make Islamic knowledge more accessible to those without specialized knowledge in Islamic studies.
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