> For the complete documentation index, see [llms.txt](https://docs.unitlab.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.unitlab.ai/documentation/workflows/review-rework-and-escalation.md).

# Review, rework, and escalation

Route human decisions, Consensus disagreements, and benchmark exceptions to an accountable correction or review owner.

Review turns an acceptance decision into a workflow transition. Rework turns specific feedback into corrected annotations. Escalation assigns a decision that exceeds the current policy or expertise to an appropriate owner.

Use [Review Stages](https://docs.unitlab.ai/documentation/qa/review-stages) for the complete reviewer procedure and [QA Workflows](https://docs.unitlab.ai/documentation/qa/qa-workflows) for combined quality-control patterns.

## Configure a correction loop

```mermaid
flowchart LR
  A[Annotate] --> R[Review]
  R -->|Approved| C[Complete]
  R -->|Rejected| A
```

Connect the Review approval route to the next required check or Complete. Connect rejection to the intended annotation or correction stage. Add a named Review stage when another specialist must make a separate decision, then configure its eligible reviewers and return path.

## Keep quality outcomes distinct

| Trigger                                   | Required handling                                                                                         |
| ----------------------------------------- | --------------------------------------------------------------------------------------------------------- |
| Reviewer rejects a correctable defect     | Return it with actionable feedback, then review the correction.                                           |
| Consensus fails the agreement requirement | Send it to Review and Refine through a Review stage, preserving the independent submissions.              |
| Quality Gate fails                        | Investigate the submission and approved reference, then follow the configured correction or review route. |
| Quality Gate cannot evaluate              | Follow Not evaluated. Do not label missing comparison evidence as a passed or failed benchmark.           |
| Instructions are ambiguous                | Ask the policy owner to resolve the rule and identify other affected work.                                |
| Source data is unusable                   | Apply the explicit source-exclusion or archive policy.                                                    |

## Operate the handoff

1. Inspect all relevant source context and the current instructions.
2. Identify the specific instance, boundary, timing, field, property, or relationship needing attention.
3. Correct it if the review policy permits, or leave an anchored issue that explains the expected change.
4. Use Approve or Reject as appropriate and confirm the destination and owner.
5. On return, check that the stated defect and related inconsistencies are resolved.
6. Escalate recurring policy or ontology gaps through controlled updates and team calibration.

Saving a correction does not complete a review transition. Resolving a comment does not by itself approve the item. Consensus adjudication additionally requires explicit approval of retained submitted objects and Item Properties; follow [Consensus](https://docs.unitlab.ai/documentation/qa/consensus).

## Escalate through configured responsibilities

Escalation is an operating path, not a universal Workbench action. Use an appropriate specialist Review stage or an authorized manager handoff. Give the specialist the source, disputed labels, relevant instruction, and question to decide. Define how the item returns to annotation, review, or completion after that decision.

Monitor repeated rejection reasons and inspect the affected cohort when a defect suggests a systemic policy problem. Keep [Project Instructions](https://docs.unitlab.ai/documentation/projects/project-instructions), ontology choices, calibration examples, and workflow ownership consistent.

## Next steps

* [Stages and routes](https://docs.unitlab.ai/documentation/workflows/stages-and-routes)
* [Review Stages](https://docs.unitlab.ai/documentation/qa/review-stages)
* [Quality Gate](https://docs.unitlab.ai/documentation/qa/quality-gate)