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Relevance 8/10Safety and PolicyBeginner6 min read
Content Moderation Labeling
Content moderation labeling classifies content by policy categories and severity.
Why it matters for annotators
Moderation datasets are central to trust and safety systems.
Visual mental model
Content -> violation taxonomy -> category/severity label.
Examples (bad vs good)
Scenario: Real annotation scenario involving Content Moderation Labeling
Bad: Labeling quickly without applying project rubric.
Good: Applying rubric criteria, documenting rationale, and escalating uncertainty.
Common mistakes
- Skipping guideline details for edge cases.
- Applying inconsistent criteria across similar samples.
- Avoiding escalation even when uncertain.
Submission checklist
- Read the latest guideline update before each batch.
- Apply rubric dimensions explicitly in each decision.
- Escalate ambiguous items with concise rationale.