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Lesson #60 of 70
Agentic AI & RAG9 min readAdvanced
Knowledge Graph RAG (GraphRAG) & Multi-Hop Entity Reasoning
Extract entities and relations, construct property knowledge graphs in Neo4j, and execute multi-hop reasoning queries that traditional vector search cannot answer.
Works with:Microsoft GraphRAGNeo4j / CypherNetworkXLlamaIndex PropertyGraph
Key Takeaways
- Vector search struggles with global dataset questions ("What are the top 5 overarching supply chain risks across all vendor contracts?")
- GraphRAG extracts (Subject, Predicate, Object) knowledge triples and builds hierarchical entity clusters
- Hybrid Graph-Vector querying combines semantic passage similarity with multi-hop graph traversals (Cypher queries)
- Community summaries synthesize high-level thematic intelligence across entire corpus clusters
The Diagnostic Context
When answering complex relational questions spanning 50 different documents (e.g. "Which suppliers in Region A depend on microchips produced by Company B?"), vector search returns fragmented snippets. GraphRAG structures unstructured text into a queryable knowledge graph.
The Core Technique
Constructing Knowledge Triples for GraphRAG
PYTHON
from pydantic import BaseModel, Field
class KnowledgeTriple(BaseModel):
subject: str = Field(description="Entity node initiating the relationship")
predicate: str = Field(description="Relationship verb/type in UPPERCASE_SNAKE_CASE")
object: str = Field(description="Target entity node")
confidence: float = Field(ge=0.0, le=1.0)
class ExtractedGraphData(BaseModel):
triples: list[KnowledgeTriple]
entities: list[str]
# Example Cypher Query for Multi-Hop Graph Traversal in Neo4j:
# MATCH (c:Company {name: "Apex Semiconductor"})-[:SUPPLIES_TO*1..3]->(target:Company)
# RETURN target.name, target.country
Global Search vs Local Search in GraphRAG
- Local Search: Focuses on specific entity neighborhoods (e.g., "What are the contractual terms for Vendor X?").
- Global Search: Aggregates pre-computed community summaries across the entire graph to answer broad thematic questions (e.g., "What are the common vulnerabilities in our 2026 cloud architecture?").
5-Minute Activation Challenge
Try This Right Now
Extract 5 knowledge triples from a short press release about an acquisition (e.g. Company A acquired Company B for $500M led by CEO C) and visualize them as nodes and edges!
Tip: Knowledge only becomes capability once you run the prompt yourself.
Comprehension Check
Test Your Instincts (1 Questions)
1