> ## Documentation Index
> Fetch the complete documentation index at: https://arize-ax.mintlify.site/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Assign to a Labeling Queue
> Route spans to your team for structured human review and annotation
export const AskAlyx = ({children}) => {
const gradientId = `askAlyxGradient-${Math.random().toString(36).slice(2)}`;
return ;
};
Instead of telling your team "go look at traces from yesterday," create a **labeling queue** with the specific spans or traces that need review — a structured list with an annotation schema and progress tracking.
**Ask Alyx** to create a labeling queue for you — try *"Create a queue for spans flagged by the safety eval."*
## Add spans to a queue
**Individual:** Open a span → click **Add to** → **Labeling Queue** → choose or create a queue.
**Bulk:** Select multiple spans in the traces table → **Add to** → **Labeling Queue**.
\[screenshot: add to labeling queue menu from span toolbar]
## The review workflow
1. Open **Annotation Queues** from the left sidebar
2. Select a queue → review each record's inputs, outputs, and existing evals
3. Add annotations using the queue's annotation config
4. Move to the next record
\[screenshot: annotator queue view with span details and annotation form]
A queue record can be a single **span** or an entire **trace**. When you annotate a trace-level record, the label is written as a [trace-level annotation](/docs/ax/observe/take-action/annotate-traces#span-level-and-trace-level-annotations) rather than on an individual span — use it when the judgment covers the whole request or conversation.
## From queue to dataset
After labeling, create a dataset from the annotated results for experiments and fine-tuning.
**With human review:** Traces → Labeling Queue → Annotate → Dataset
**Without human review:** Traces → [Dataset](/docs/ax/observe/take-action/curate-dataset) directly
## Manage queues via API
You can create and manage annotation queues programmatically using the GraphQL API. This is useful for automating queue creation in CI/CD pipelines or building custom tooling.
```graphql theme={"theme":{"light":"github-light-default","dark":"github-dark-default"}}
mutation {
createAnnotationQueue(input: {
projectId: "PROJECT_ID"
name: "Weekly Safety Review"
description: "Spans flagged by safety eval for human review"
}) {
annotationQueue { id name }
}
}
```
The Python SDK (v8+) supports creating **annotation configs** programmatically. Annotation queue management via SDK is planned — use the GraphQL API in the meantime.