FIGR / UI TEMPLATE
Review agreement, label drift and annotator notes for training datasets.
This table template covers ai product operations & evaluation workflows inside an existing product. All people, records and metrics shown are fictional.
BUILD ON THIS
Explore this screen, then bring in your own product and design system to shape the next version.
Table
Audit dataset labels
table workflow
Default, Selected, Filtered, Empty, Warning, Success
Independent product UI reference; no external / 1mg design system
Review agreement, label drift and annotator notes for training datasets. The user needs to audit dataset labels without losing context.
Product areas: AI Overview, Evaluations, Runs, Datasets, Policies. Task fields: AI Product Operations record, Assigned owner, Product area, Review status. Example metrics: Active records, Items needing review, Within policy, Upcoming deadlines.
Default, Selected, Filtered, Empty, Warning, Success. Also cover restricted access, interrupted saves and missing or stale data when relevant.
AI Overview → Dataset Label Quality Audit → Audit dataset labels
table, filters, status, record details, review actions
Keep critical columns, sorting, filters and row context visible.
Review audit dataset labels with a case such as DATA-812 · low agreement. Make room for empty, warning, permission-denied and failed-save states.
Adapt Dataset Label Quality Audit to my existing product and design system. Keep our current screens, components and role rules. Explore default, selected, filtered, empty, warning, success and relevant edge cases before generating editable Figma-ready UI.
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Browse other product UI examples, compare patterns, and pick the direction that suits your product.