Back to Academy
Relevance 8/10Prompting and EvaluationIntermediate6 min read
Pairwise Ranking
Pairwise ranking compares two candidate outputs and chooses the better one.
Why it matters for annotators
It is a core pattern for preference and reward data creation.
Visual mental model
Candidate A vs B -> rank -> rationale.
Examples (bad vs good)
Scenario: Real annotation scenario involving Pairwise Ranking
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.