Linking Hadith Narrator Identities Across Heterogeneous Arabic Biographical Databases: A Multi-Signal Entity Resolution Pipeline

📅 2026-06-30
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🤖 AI Summary
This study addresses the challenge of identity linkage among hundreds of thousands of Islamic hadith transmitters across heterogeneous Arabic biographical databases, where the absence of unified identifiers impedes cross-resource integration. To resolve this, the work proposes the first cross-database, multi-signal entity resolution framework tailored for Arabic hadith transmitters. The approach employs a two-stage pipeline: first linking transmitters from the Sanadset corpus to the HadithTransmitters database via name similarity, then aligning with the MuslimScholars database through a weighted fusion of multiple signals—namely name, death year, and reliability rating—augmented by a transitive linking strategy. Operating without metadata, the framework achieves high-coverage identity resolution, constructing a directed transmission graph comprising 185,216 nodes and 814,093 edges. This effort yields the first structured integration of these three major resources, accompanied by the public release of high-quality linked corpora and a cross-source biographical knowledge graph.
📝 Abstract
The transmission chains (sanad) of Islamic Hadith literature encode relationships among tens of thousands of historical narrators whose biographical records are dispersed across independently maintained digital databases that share no common identifier. We present a two-phase entity resolution pipeline that links narrator names from the Sanadset 650K corpus - 650,986 Hadith records from 926 books containing 185,216 unique narrator name variants - to two biographical databases: Hadithtransmitters (Hawramani; 100,915 entries) and Muslimscholars (25,247 entries). Phase 1 matches Sanadset names to Hawramani using name-only similarity (Sanadset carries no metadata), yielding 94,628 links (51.1%; HIGH 39,938 / MED 54,690). Phase 2 cross-references Hawramani against Muslimscholars via a weighted multi-signal function combining name similarity, death-year proximity, and reliability grade polarity, yielding 95,573 links (94.7% of Hawramani; HIGH 18,245 / MED 71,546 / LOW 5,782). Chaining the two phases gives Sanadset narrators transitive access to Muslimscholars data. The linked data enable construction of a 185,216-node, 814,093-edge directed transmission graph enriched with cross-source biographical metadata. The annotated link corpora and enriched graph are released as open resources.
Problem

Research questions and friction points this paper is trying to address.

Hadith
Entity Resolution
Biographical Databases
Narrator Identity
Arabic Text
Innovation

Methods, ideas, or system contributions that make the work stand out.

entity resolution
multi-signal matching
Hadith narrator linking
heterogeneous database integration
transmission graph
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T
Taufiq Wirahman
Research Center for Computing, National Research and Innovation Agency (BRIN), Soekarno Science and Technology Zone, Cibinong, West Java, Indonesia; Department of Mathematics, Faculty of Sciences, Universiti Teknologi Malaysia, Johor Bahru, Malaysia