Process of identifying, structuring, and representing connections between entities in data to enable semantic understanding and contextual retrieval.
Key Components
- Entity Extraction: Identifying key concepts (e.g., people, organizations, events) from unstructured data
- Relationship Extraction: Detecting semantic links between entities (e.g., “works_for”, “located_in”)
- Graph Structure: Representing entities as nodes and relationships as edges in a Knowledge Graph
Integration with LLM RAG
- Cocoindex framework enables real-time knowledge graph construction from markdown documents using LLMs
- Processes document collections to extract entities/relationships → stores in Neo4j for dynamic rag context
- Enhances LLM query accuracy by providing structured semantic relationships instead of raw text
- Example: Building a knowledge graph from technical documentation to improve “explain” queries in RAG systems
Backlink
2026 04 14 Cocoindex channel and knowledge Graphs for LLM RAG