Beyond Vector Search: Building a Deterministic 3-Tiered Graph-RAG System

A tutorial on building a deterministic three-tiered Graph-RAG system that combines a lightweight QuadStore knowledge graph with a ChromaDB vector database to reduce factual hallucinations. The architecture uses three priority layers: absolute graph facts (SPOC quads), statistical graph data, and vector documents as fallback. Instead of complex algorithmic routing, all three sources are queried simultaneously and a prompt-enforced hierarchy instructs the language model to resolve conflicts deterministically. The system is demonstrated using fabricated NBA data with a local Llama 3.2 3B model via Ollama, showing how Priority 1 facts override conflicting lower-tier data.