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Google's Knowledge Graph is a structured entity database that maps real-world objects - people, places, organisations, and concepts - to semantically rich attribute sets and inter-entity relationships, replacing string-matched keyword lookup with disambiguated, meaning-based retrieval. The system resolves lexical ambiguity (e.g., "Taj Mahal" as monument vs. musician vs. restaurant) by anchoring queries to canonical entities with unique identifiers, drawing from synthesised sources including Freebase, Wikipedia, and the CIA World Factbook to populate typed properties and relational edges. This shifts ranking and indexing logic from document-to-keyword co-occurrence toward entity-to-entity graph traversal, enabling query expansion, direct answer surfacing, and contextual result clustering without requiring exact-match signals in crawled content.