An exploration of how structured data serves as the ‘Grounding Wire’ for Retrieval-Augmented Generation (RAG) systems, preventing hallucinations and enabling deterministic output from probabilistic models.

An analysis of how Large Language Models ingest and utilize structured data during pre-training, moving beyond ’text-only’ ingestion to understanding the semantic backbone of the intelligent web.