Do these 3 things before closing this tab:
1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsDo not let a graph silently choose which source is true. Keep each claim tied to its supporting passage, source, scope, and time; investigate why claims disagree; then either apply a documented source policy or show the unresolved conflict with evidence. When a source changes, refresh the graph material derived from it while retaining earlier versions if users need historical answers.
Why Graph RAG can return conflicting or outdated facts
A knowledge graph organizes extracted entities, relationships, and descriptions; it is not, by itself, a system for deciding which source is authoritative. If two documents disagree, both may be represented in the graph. If an underlying document changes, earlier extracted claims or generated summaries may also remain available until the dependent material is refreshed.
As an Amazon Associate I earn from qualifying purchases.
Microsoft’s GraphRAG documentation describes a pipeline that carries information from source documents and text units into extracted graph data, claims, communities, reports, and embeddings. Those downstream artifacts can preserve a stale statement or blur a disagreement if they are not refreshed or checked against the source. The standard pipeline summarizes entity and relationship descriptions; claim extraction is a separate, optional feature and is off by default. Microsoft notes that it generally requires prompt tuning.
Free tools Windows power users keep installed
One-click scans. No signup required.
This is why a concise graph summary should not be treated as the only evidence. Keep the original passage available so a reviewer or answer-generation step can verify what the source actually said.
#1 Best Overall
What to store so every claim can be checked
Represent source-grounded statements separately rather than overwriting one value with a blended entity summary. A practical claim record can include:
- The assertion: subject, predicate, and object or value, plus the extracted claim text.
- Its evidence: a stable document identifier, text-unit or passage identifier, and the passage itself or a reliable pointer to it.
- Its source context: source identity, publication or effective date when known, and document version or retrieval date.
- Its applicability: jurisdiction, organization, product version, population, or other scope that affects whether the statement applies.
- Its time information: the period the claim is said to be true, if established, and its status, such as active, superseded, or unverified.
- Its extraction context: the extraction method or prompt version, where useful for diagnosing interpretation errors.
The specific fields beyond the status and time bounds described in Microsoft’s GraphRAG dataflow are implementation choices, not required GraphRAG defaults. Microsoft describes claims as positive factual statements with an evaluated status and time bounds. Its dataflow also links documents and text units, supporting passage-level provenance.
For systems that answer historical questions, distinguish valid time—when a fact applied in the world—from record time—when the system ingested or recorded it. This bitemporal distinction is a design recommendation, not a documented GraphRAG default. It helps answer both “What is the current policy?” and “What did the system know on this date?” without overwriting history.
Quick wins for a faster PC:
Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Clear out junk files and repair common Windows errorsFree Scan →Rank #2
How to diagnose a disagreement before choosing a source
Compare the claims and their cited passages first. Then classify the difference; the reason determines whether the claims truly conflict and what should happen next.
- Temporal: The claims apply to different dates, policy periods, or product versions. Preserve both if a historical answer may be needed, and use the relevant time window for the query.
- Scope-related: The claims describe different regions, groups, organizations, products, or definitions. Add or correct the missing scope instead of treating one statement as universally true.
- Source contradiction: The sources address the same scope and period but make incompatible assertions. Compare their evidence and authority for that particular subject; if they remain incompatible, disclose the dispute.
- Extraction or interpretation error: The graph assertion overstates, misreads, or loses a qualification from its cited passage. Correct or remove the assertion and review whether the extraction prompt or process needs adjustment.
- Coverage gap: The available passages do not establish which claim applies. Do not infer a winner from incomplete evidence; qualify the answer or abstain.
This is a practical classification for investigation, not a reproduction of the exact category names in Google Research’s 2025 paper “(D)RAGged Into a Conflict.” That work supports the broader point that conflict types can call for different handling: in its experiments, providing a model with a conflict category improved response quality and appropriateness, though the authors also report room for improvement.
How to decide which source to use
Use a written source policy rather than an invisible “newest source wins” rule. Assess each source against the question being asked, considering:
- Whether the cited passage directly supports the claim, including its qualifications.
- Whether the source is authoritative for this domain and decision.
- Whether it is final, current, and in force, rather than a draft, proposal, or superseded version.
- Whether its jurisdiction, product, population, and time period match the question.
- Whether a later source explicitly replaces the earlier one.
Recency is evidence to consider, not an automatic truth score: a recent draft does not necessarily replace an older policy that remains in force. The reviewed sources do not establish a universal source hierarchy or scoring formula, so define and document rules appropriate to your corpus. When two relevant, authoritative sources still conflict, retain both with their dates and scopes and explain what remains unresolved.
How to update the graph when a source changes
Treat a document change as a dependency update, not merely as a file replacement. A practical refresh sequence is:
- Version the changed document. Keep its stable source identity and record the new version or retrieval date. Mark the earlier version as superseded when that is supported, rather than deleting it if historical questions matter.
- Find dependent material. Identify text units, claims, entities, relationships, summaries, reports, or embeddings derived from the changed passage.
- Reprocess the changed text. Recreate or update the relevant extracted assertions and keep each one linked to its supporting passage.
- Refresh affected summaries and indexes. Regenerate material that depends on the changed facts so stale statements do not survive only in a summary, report, or embedding.
- Check the result against the source. Confirm that the updated claims preserve qualifications, scope, and dates, and that old claims are retained, superseded, or removed according to policy.
- Run targeted queries. Test current and historical questions, including queries that should surface a disagreement or the updated source.
Microsoft documents the relationships among source documents, text units, extracted graph data, claims, communities, reports, and embeddings, but does not prescribe one universal invalidation policy. The refresh sequence above is system-design guidance based on those dependencies; implementation details depend on how an index tracks lineage and supports partial or full reprocessing.
How to answer when the evidence does not settle the conflict
If evidence and policy support one claim for the requested scope and date, answer with that claim and state the relevant qualification. If competing evidence survives review, describe the disagreement and cite each source passage so the reader can inspect both. If the corpus does not establish an answer, say so rather than silently selecting a winner.
Microsoft’s GraphRAG Responsible AI Transparency guidance says human analysis matters for reliable insights and recommends tracing provenance to verify generated inferences. That makes provenance useful not only for debugging but also for explaining an answer’s limits to the reader.
How to evaluate conflict handling
Build an evaluation set from real contradictions and source changes in the target corpus. Include cases where a fact changes over time, where scope explains an apparent contradiction, where the graph extraction misreads a passage, and where the evidence is genuinely inconclusive. Check whether the system:
Best Value
- Retrieves the competing claims and their source passages.
- Preserves dates, scope, and supersession status in the answer.
- Answers “as of” questions using the appropriate historical evidence.
- Refreshes summaries and other derived material after a source changes.
- Explains an unresolved conflict or abstains when the evidence is insufficient.
Inspect claim-level evidence as well as the final generated response. Microsoft describes evaluation practices that include manual inspection, gold answers, answer coverage, returned-context review, and claim coverage with source inspection. Google Research’s 2025 work argues that evaluation should test conflict management as well as factual accuracy. The reviewed sources do not set a universal pass threshold for a particular application; establish one against the risks and needs of your corpus.
What the GraphRAG implementation choice does—and does not—mean
Microsoft documents different extraction choices, but none should be mistaken for an automatic conflict-resolution guarantee.
| Approach | What the reviewed material establishes | Implication for conflicting or dated claims |
|---|---|---|
| Standard GraphRAG | Uses an LLM for entity and relationship extraction and summarization. Claim extraction is optional and off by default; it generally requires prompt tuning. | Claims can be useful for explicit evidence handling, but the default summary-oriented pipeline does not itself settle source disagreements. |
| FastGraphRAG | Substitutes some LLM reasoning with NLP and co-occurrence extraction and does not use claim extraction. | Do not assume it provides the same claim-level representation or conflict handling as a configured standard pipeline. |
| T-GRAG | A research proposal using timestamped evolving graphs and temporal query decomposition. | It addresses temporal ambiguity as a research approach; it should not be presented as equivalent to a production-validated GraphRAG product. |
Microsoft also cautions that effective indexing depends on well-constructed prompts and that domain-specific concepts may need tailored prompts. Its responsible-use guidance says GraphRAG works most effectively with natural-language text focused on an overall topic and rich in identifiable entities. These conditions affect extraction quality, but they do not replace evidence review or a source policy.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
