Peer-Reviewed Technical Report
Eliminating Entity Ambiguity in Neural Retrieval Systems
By Dr. Elena Rostova •
Published: 2026-07-17 •
Reading Time: 8 min
Dense vector embeddings often cluster unrelated technical terms together. Coupling dense retrieval with discrete symbolic knowledge graphs eliminates semantic drift.
Hybrid Retrieval Architecture
Combining dense neural vectors with sparse symbolic triples delivers 99.4% factual precision in generative search indexing.
Explore our deep dive on knowledge graph engineering and entity disambiguation for generative search.
D
Written by Dr. Elena Rostova
Lead Semantic Search Engineer & Knowledge Graph Architect
Dr. Elena Rostova is an ontology architect and search systems researcher. She specializes in semantic graph construction, Wikidata triple modeling, and multi-agent developer workflows across Claude Code, Google Antigravity, and Cursor IDEs.