What is Knowledge Graph?
Knowledge Graph — A network of real-world entities and their relationships, used by AI to understand context and facts.
Knowledge graphs represent information as entities (nodes) and relationships (edges). They help AI systems understand that ‘Apple’ the company is different from ‘apple’ the fruit based on context and connections. They power features like Google’s Knowledge Panel.
Frequently Asked Questions
How does a knowledge graph help AI?
It provides structured context that helps AI disambiguate entities, understand relationships, and reason about facts — reducing hallucinations and improving answer accuracy.
How do I build a knowledge graph?
Start with your existing structured data (databases, CRMs). Use NER to extract entities from unstructured text. Define relationship types and connect entities. Tools like Neo4j and Amazon Neptune help manage graph data.
Can I combine knowledge graphs with LLMs?
Yes, this is a powerful pattern. The knowledge graph provides structured facts while the LLM handles natural language understanding and generation. This hybrid approach is called Graph RAG.