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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

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Clipboard semantic evidence adjudication v1

Review only the fields listed in unresolvedFields. Judge from the text itself; do not inspect previous model votes, source labels, or another adjudicator.

Return one JSON object per input record:

{
  "id": "same id",
  "resolutions": {
    "task": "true",
    "ambiguous": "false"
  },
  "confidence": {
    "task": 0.97,
    "ambiguous": 0.94
  },
  "evidence": {
    "task": "send the report",
    "ambiguous": "by Friday"
  }
}

Requirements:

resolutions, confidence, and evidence must contain exactly the fields in unresolvedFields.
Intent and flag values are true, false, or unknown.
Sentiment values are positive, neutral, negative, or unknown.
Evidence must be a short exact quote copied from the input text.
Use unknown when the text alone does not justify a decision.
Confidence is per field and must be between 0 and 1.
Do not output explanations, markdown, or additional fields.

Use the boundaries from labeling-instructions-v2.md. In particular, distinguish requests from personal plans, genuine information questions from request-shaped commands, direct messages from terminal notices, and expressed wishes from quoted, future, sarcastic, or received blessings.

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Clipboard semantic evidence adjudication v1

1.3 KiB

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