Phase C is the first phase where operator-authored exemplar corpora
become engine-derived recognizer proposals automatically. The math
thesis ("decodes, not generates") manifests in the math lane here.
Modules
- teaching/exemplar_ingest.py — pure-function loader for Phase B
exemplar JSONLs. ExemplarCorpus carries a sha256 digest over its
canonical (sorted-by-exemplar_id, sort-keyed) bytes.
- teaching/recognizer_synthesis.py — per-category synthesizers
(_synthesize_descriptive_setup_no_quantity / _temporal_aggregation /
_rate_with_currency) distil a corpus into one RecognizerSpec.
Determinism: same corpus -> byte-identical spec. Narrowness: the
spec records only observed sub-shapes; an out-of-corpus currency
symbol or window unit does not match. Phase B author_notes surface
in canonical_pattern.unresolved_notes — never silently dropped.
- teaching/contemplation.py — contemplate_exemplar_corpus(corpus)
returns a DiscoveryCandidate whose proposed_chain encodes the
RecognizerSpec as a synthetic four-field chain plus the full
recognizer_spec submap. Evidence cites every exemplar's case_id.
- teaching/replay.py — run_admissibility_replay_gate(spec, *,
active_corpus_path=None) runs cognition + G1..G5+S1 + GSM8K
train_sample. In-process baseline cache keyed on the active
corpus digest. WRONG-COUNT INVARIANT: if a candidate run lifts
the GSM8K train_sample wrong count, gate returns
replay_equivalent=False with
regressed_metrics=["gsm8k_train_sample_wrong_count"].
- teaching/source.py — ProposalKind widened with "exemplar_corpus";
exhaustive-match docs + tests updated.
CLI
- core teaching propose-from-exemplars <path> [--all] [--review-date]
[--log] [--json]. Routes the candidate through the existing
propose_from_candidate path with the admissibility gate substituted
for the cognition-only run_replay_equivalence. Never auto-accepts;
proposals land as pending for operator review.
Tests (38 new)
- tests/test_exemplar_ingest.py (12) — load, digest stability,
malformed-record rejection, file-name binding, read-only purity.
- tests/test_recognizer_synthesis.py (16) — determinism, purity,
per-category subsumption, narrowness (out-of-corpus seeds rejected),
author_notes surfaced.
- tests/test_admissibility_replay_gate.py (6) — happy path, cache
hit/invalidation, WRONG-COUNT INVARIANT regression, capability-axis
regression, cognition regression.
- tests/test_propose_from_exemplars_cli.py (4) — single corpus, --all,
determinism, read-only snapshot.
Acceptance evidence (dry run)
- All three Phase B corpora produce replay_equivalent=true,
wrong_count_delta=0. Proposal IDs:
descriptive_setup_no_quantity: 59223f13722f906a1cf9b65d9b01c990
rate_with_currency: 46ce297f797ff16da12db5de422ca3c9
temporal_aggregation: a3b892546977c5f0f64c578d6052adbd
- G1..G5+S1 wrong=0 unchanged; GSM8K train_sample 3/47/0 unchanged.
- core test --suite smoke -q: 67 passed.
- uv run core eval refusal_taxonomy: case_digest
d030f826cb0f4088771d90c52c8be2ff75054ab27c7d47eae8dbfe1225b2eea1
unchanged.
Cross-refs: ADR-0163 (Phase C), ADR-0057 (gating discipline),
ADR-0151 (auto-proposal), ADR-0152 (learning-arc), ADR-0149/0154
(recognizer pipeline), ADR-0094 (ProposalSource), Phase A PR #297,
Phase B PR #298.
Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
