The document outlines five steps for implementing search with a knowledge graph to improve enterprise search, discovery, and contextual understanding. The process begins with analyzing content sources, defining user needs, and understanding how information is related across systems. Organizations then develop an ontology that models classes, attributes, and relationships to support user questions and scalable search experiences. The next step focuses on designing intuitive search interfaces using best practices, knowledge panels, entity recognition, and natural language processing to deliver contextual and action-oriented results. Data is then ingested through ETL pipelines, transformed into graph structures, and enriched using taxonomy and NER techniques. Finally, organizations implement,

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