When Entity Resolution Stops Short, Graph Search Exposes Duplicate Networks and Coverage Gaps
Blog post from TigerGraph
Entity resolution (ER) quality issues often remain undetected because traditional review methods focus on individual records rather than the broader network, leading to incomplete coverage and misplaced confidence in the results. Problems such as duplicate identities, split clusters, and coverage gaps arise from structural deficiencies that flat views cannot expose, and these issues persist despite model updates and rule changes. Graph search enhances ER quality assurance by providing a structural perspective, allowing teams to explore neighborhoods and connection patterns around resolved entities, thereby exposing missing links and incomplete resolutions. This shift from correctness to completeness helps in identifying duplicate networks, split clusters, and coverage gaps, which are often invisible in record-level reviews. TigerGraph facilitates these processes by supporting scalable graph searches across various relationships, preserving path-level evidence for quality assurance and remediation, and enabling operational exploration of identity structures to ensure complete ER coverage, especially in contexts like fraud detection and anti-money laundering investigations.
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