The Rise of Semantic Entity Resolution

Semantic entity resolution utilizes language models to automate the deduplication of records, a critical and difficult step in building knowledge graphs from text. This process is essential for powering autonomous agents, as they require clean, resolved knowledge graphs to function effectively. The method improves upon traditional techniques by using deep embeddings and semantic clustering for blocking, and generative AI for matching and merging duplicate nodes and edges. By leveraging modern transformer models, this approach gains a deeper contextual understanding of data's meaning to create more accurate knowledge representations.