{
  "id": "topic:graph-rag",
  "_kind": "Topic",
  "_file": "domain/topics/topics-knowledge-patterns.yaml",
  "_cluster": "domain",
  "attributes": {
    "displayName": "Graph RAG",
    "description": "Graph RAG as a cross-cutting topic — combining knowledge graphs with\nretrieval-augmented generation for multi-hop reasoning over structured\nand unstructured data. Covers Microsoft's GraphRAG pattern (community\ndetection, summarization hierarchies, global search), entity-relation\nextraction from documents into graph form, graph traversal as retrieval,\nand the advantage over flat vector RAG for questions requiring synthesis\nacross multiple documents or reasoning about relationships between\nentities. Graph RAG excels at \"what is the overall theme?\" queries\nthat flat retrieval cannot answer.\n"
  },
  "outgoingEdges": [
    {
      "from": "topic:graph-rag",
      "to": "domain:software-engineering",
      "kind": "applies_to"
    },
    {
      "from": "topic:graph-rag",
      "to": "specialization:ai-agents-conversational",
      "kind": "applies_to"
    },
    {
      "from": "topic:graph-rag",
      "to": "domain:data-science",
      "kind": "applies_to"
    }
  ],
  "incomingEdges": [
    {
      "from": "domain:knowledge-management",
      "to": "topic:graph-rag",
      "kind": "contains"
    },
    {
      "from": "retrieval-pipeline:decision-graph-query",
      "to": "topic:graph-rag",
      "kind": "relates_to_topic"
    },
    {
      "from": "retrieval-pipeline:multi-hop-reasoning",
      "to": "topic:graph-rag",
      "kind": "relates_to_topic"
    },
    {
      "from": "retrieval-pipeline:graph-rag",
      "to": "topic:graph-rag",
      "kind": "relates_to_topic"
    },
    {
      "from": "topic:knowledge-graph-construction",
      "to": "topic:graph-rag",
      "kind": "related_topics"
    }
  ]
}