GraphRAG Interactive Lab — Graph-Grounded Retrieval & LLM Answers

See how graph retrieval produces connected evidence, then answer deterministically or with an optional LLM over the same context.

GuidedNo API keys in LabGraphRAG

Core idea

Graph retrieval is the constant. LLM answer generation is optional.

Mode

Mode comparison

Graph retrieval
Graph-grounded: ✓
GraphRAG + LLM: ✓
Relevant subgraph
Graph-grounded: ✓
GraphRAG + LLM: ✓
Graph context
Graph-grounded: ✓
GraphRAG + LLM: ✓
LLM
Graph-grounded: —
GraphRAG + LLM: ✓
Answer
Graph-grounded: Deterministic
GraphRAG + LLM: Observed model output

Stage	Graph-grounded	GraphRAG + LLM
Graph retrieval	✓	✓
Relevant subgraph	✓	✓
Graph context	✓	✓
LLM	—	✓
Answer	Deterministic	Observed model output

Choose an example

Examples replay frozen measured executions. No live API call is made.

Entity RetrievalResolve an entity, then retrieve people connected through an explicit relationship.Multi-Hop RetrievalFollow measured multi-hop paths so hop 2 can fan out to multiple neighbors.Relationship-Grounded AnswerAnswer from connected graph relationships, not merely similar text.No Relevant SubgraphWhen no relevant subgraph exists, there is no grounded graph evidence for an answer.

Replays a frozen measured execution; no live API call is made.

Choose a mode and example to replay the measured GraphRAG execution.

Previous Lab

Continue from SPARQL UPDATE into graph-grounded retrieval.

← SPARQL Updates & Graph Mutation

Continue Learning

Guides that explain GraphRAG, knowledge graphs, and retrieval.

Implementation

Run the measured Cookbook example locally.

GraphRAG Cookbook

Related Tools

Tools commonly used with knowledge graphs.

Related Rankings

See how this stack compares in DataAIHub rankings.

Best Knowledge Graph Platforms

Lab ID knowledge-graph-graphrag · guided / precomputed