A Novel LLM-Based Approach for Automated Seerah-Hadith Mapping: Connecting Islamic Historical Narratives Through Vector Search and Semantic Analysis

Mushfiqur Rahman Talha, Mohammad Galib Shams, Riasat Islam, Nabil Mosharraf

Keywords: Seerah, Hadith, Text mapping, Relationship between texts, Seerah references

TL;DR: This paper introduces an LLM-based method to automatically map related hadiths to specific events in Seerah, making Islamic knowledge more accessible by using vector search and semantic analysis for enhanced scholarly research.

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.

Submission Number: 3