The short answer
GraphRAG uses relationships to help retrieve or organize context.
Inspect each relationship and its supporting source.How does GraphRAG use relationships?
GraphRAG uses graph structure to help retrieve or organize the context supplied to a generative model. A relationship can connect a question about one entity to supporting evidence in another document.
The term covers several approaches. Some traverse entity relationships. Others use graph-derived summaries to answer broader questions. A graph database alone does not define the complete retrieval and generation workflow.
Trace a question across three documents
Our fictional Project Alder depends on the Kestrel access review. The review follows the Monday schedule. Only the schedule states the inspection date.
Project Alder
depends on: Kestrel access review
follows: Monday schedule
source fact: inspection on 18 OctoberThis is a reading aid, not import syntax. In the fixture, the second connection uses the supported depends_on relation. Its authored interpretation retains the original "follows" passage.
| Step | Supporting passage | Inspection needed |
|---|---|---|
| Project to review | project.md | Does the source name this dependency? |
| Review to schedule | review.md | Does the relation preserve the source's meaning? |
| Schedule to date | schedule.md | Is this the current document version? |
A complete path helps locate the date. It does not prove that the inspection will happen or that every authored relationship is correct.
Distinguish the graph's different jobs
Reranking changes the order of existing retrieval candidates. Expansion follows relationships and can add evidence beyond those candidates. A context traversal can assemble a bounded set of related records for a task.
These mechanisms have different failure modes. Reranking cannot recover a source it never considers. Expansion can follow a wrong relationship. Broad traversal can provide more context than the task needs.
Our four-mode experiment compares the local service's retrieval configurations. Check its interface and evidence limits before generalizing to another integration.
Observe what happens when support changes
We reproduced a hybrid retrieval and graph-expansion demonstration against Gigabrain's System and Full 1.1.0 archives. It reached the connected schedule and returned its passage.
The fixture then changed its disposable schedule from 18 October to 25 October. The old citation failed verification. The stale path stayed unavailable until the fixture supplied updated support.
The recorded path and receipts show that sequence. The experiment uses authored fictional graph records and retrieved quotations. It does not measure extraction by a model or generated-answer quality.
Separate this example from global summarization
Microsoft's GraphRAG research uses graph-derived community summaries to address questions about a corpus as a whole. That is a different task from following one project dependency.
A small dependency graph does not reproduce that research system. Ask which graph construction, retrieval and summarization steps a particular implementation actually performs.
The architecture comparison helps match those choices to the question you need to answer.
Review a path before relying on it
- Name the entity in your question.
- List the sources required for its answer.
- Inspect each relationship's supporting passage.
- Check the source versions.
- Repeat with one relationship missing.
- Record the unsupported boundary.
Download the relationship-path worksheet. Use the source architecture guide for the practical setup.
See Gigabrain's graph model and your agent's integration before choosing a package.
Method note: Gigabrain Labs prepared this guide with AI assistance from primary references and the linked synthetic demonstration.
