Annotation (data)
Adding labels or metadata to data records to make them more useful for downstream processing. Example: annotating a support ticket with "billing", "urgent", and "enterprise" tags added automatically by Claude AI based on message content.
Expert insight
Data annotation quality directly determines the quality of anything trained or evaluated against it, inconsistent annotation guidelines between different annotators (or the same annotator on different days) introduce noise that no amount of downstream model sophistication can fully correct for.
In a real workflow
Support tickets are labelled by a person as "billing" or "bug" to build training and evaluation data.
Common mistakes
- Inconsistent labels between annotators.
- Too few examples of rare cases.
Complexity level
Requires some familiarity with automation concepts.
Related terms
See it in action
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