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Knowledge Graph

A knowledge graph represents real-world entities and the relationships between them in a connected structure. Nodes may describe people, products, places, documents, or concepts, while edges state how those entities relate. Because relationships are explicit, systems can traverse the graph to answer questions, combine records from different sources, support recommendations, or add context to AI responses. Knowledge graphs often rely on schemas, identifiers, and rules that keep meaning consistent across data. They still require ongoing maintenance: duplicate entities, missing links, outdated facts, and uncertain sources can reduce reliability. When connected to generative AI, access controls and provenance help users distinguish verified graph data from generated interpretation.

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