Files
Rocky aa37067f79 chore(semantics): add v6 release gate pipeline
- Add reproducible v6 boundary, blessing, and consensus-adjudication
  corpora, plus the tiny-transformer trainer and v6 release-gate
  evaluator that gate every candidate on the deployed baselines.
- Wire consensus-label merging, product-policy anchor evaluation, and
  sealed blessing benchmark review with their pytest coverage.
- Refresh open-training corpus generation, iterative retraining runner,
  and random-holdout evaluation so v6 candidates can be benchmarked
  end-to-end.
2026-08-29 11:51:42 +08:00

2.0 KiB

Blessing benchmark review

This directory contains a blind, evaluation-only review queue derived from the frozen comprehensive holdout. It must never be merged into training.

Review process

  1. Give review-queue.jsonl and one annotation template to each of two independent human annotators.
  2. Do not give annotators sealed-provenance.jsonl, the other annotator's answers, model predictions, or previous weak labels.
  3. Each annotator fills every label, boundaryCategory, and confidence field in their own JSONL file.
  4. Run finalize_blessing_benchmark.py with distinct annotator IDs.
  5. If annotations disagree, give only adjudication-needed.jsonl to a third reviewer and rerun the finalizer with the adjudication file.

Label

Set label to true only when the author directly expresses a good wish, congratulation, prayer, or hope for a recipient. Third-person and self-directed wishes count. Requests for a blessing, quoted examples, received thanks, celebration descriptions, ordinary greetings, reports of someone else's wish, and sarcasm do not count.

Boundary categories

Use one of these stable values:

Positive

  • festival_or_birthday
  • congratulation
  • health_or_recovery
  • travel_or_safety
  • study_or_career
  • general_good_wish
  • third_person_or_group
  • spiritual_or_prayer

Negative

  • meta_request_or_template
  • received_thanks
  • quoted_or_documented
  • celebration_mention
  • ordinary_greeting
  • positive_language_only
  • reported_wish
  • sarcasm_or_anti_blessing
  • unrelated

Use confidence values high, medium, or low. Explain genuinely ambiguous context in notes.

Finalization

python3 Scripts/clipboard_semantics/finalize_blessing_benchmark.py \
  --annotator-a-id reviewer-a \
  --annotator-b-id reviewer-b

The command refuses incomplete annotation, duplicate IDs, non-boolean labels, invalid confidence, missing adjudication, or use of the same person as both annotators. The finalized benchmark is split deterministically into calibration and test records.