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Relevance 7/10Computer VisionBeginner6 min read
OCR Annotation
OCR annotation labels text regions and transcriptions in images and documents.
Why it matters for annotators
OCR quality influences search, document AI, and downstream extraction.
Visual mental model
Document image -> text region + transcript labels.
Examples (bad vs good)
Scenario: Real annotation scenario involving OCR Annotation
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.