December 2026
Intermediate to advanced
300 pages
3h 32m
English
Content preview from GraphRAG: The Definitive Guide
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Chapter 4. Knowledge Graph Concepts
Knowledge graphs have travelled a long road from their early academic origins to the centre of modern AI architectures. What began as an attempt to structure meaning has become an indispensable foundation for RAG, intelligent applications, and enterprise automation. Yet for many teams, the term still feels slippery: Is a knowledge graph a database? An ontology? A search system? An AI enrichment layer? A modelling discipline?
The truth, as this chapter shows, is that a knowledge graph is all of these and none of these at the same time. It is not a product category but a way of organising knowledge so that people and machines can make better decisions. The chapter you are about to read cuts through the noise by focusing on the essentials: why knowledge graphs matter, what they are, and how to think about the layers that constitute them. It acknowledges the messy reality of enterprise landscapes (multiple systems, diverging mental models, structured and unstructured ...
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