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Beyond the Chunk: How GraphRAG Teaches AI to Reason, Not Just Retrieve

DEV Community·Seenivasa Ramadurai·30 days ago
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#ai#llm#nlp#graphrag#entities#graph
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Introduction To understand knowledge graphs, you first need to grasp three core concepts: entities , relations , and triples . Imagine a knowledge graph as a network that models the real world using nodes and connections . In this network, an entity is any distinct thing or object such as a person , city , or company . For example, “Sreeni”, “Plano”, and “Caterpillar” are all entities. A relation describes how two entities are connected, such as “ lives_in ”, “ works_at ”, or “ located_in ”. Relations give meaning to the links between entities by defining how one entity is associated with another. A triple is a simple statement that combines two entities and a relation , forming a fact: for instance, (“Sreeni”, “lives_in”, “Plano”) says that Sreeni lives in Plano . Triples are the building blocks of knowledge graphs, allowing you to represent complex information as a set of simple, connected facts. Let's be real for a second.…

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