Gold standard datasets are expertly-labeled benchmarks used to measure annotator quality and detect labeling regressions.
What is a Gold Standard Dataset?
A gold standard is a set of perfectly labeled items created and verified by experts. Use them to:
- Test new annotators before certification
- Continuously spot-check ongoing annotator quality
- Detect quality drift over time
- Benchmark annotation accuracy across projects
Creating Gold Standard Training Data
- Select diverse, representative samples covering all label classes
- Have multiple domain experts label each item independently
- Resolve disagreements through discussion and consensus
- Document the reasoning for edge case decisions
- Review and update gold standards as guidelines evolve