Entity resolution (ER) is a complex process focused on connecting structured and semi-structured data sources uses for knowledge graph construction and updates. ER focuses on data quality in ways that support tracking provenance, conducting audits, and providing evidence for key decisions (e.g, in law enforcement, voter registration, etc.) with crucial impact on the quality and trust of downstream graph analytics and AI apps.

This talk shows how to use ER with open data to construct a KG in KùzuDB. We'll focus on linking multiple datasets (beneficial ownership, sanctions, GLEIF, etc.) regarding corporates in the London metro area, then explore hidden relations through graph visualization, chat interaction, and use in Graph-enhanced RAG for LLM-based chatbots.

This example illustrates KG work used in production to investigate _ultimate beneficial owner_ (UBO) and sanctions compliance.