dd3cfa3257
Lands the last load-bearing Phase 3 v2 engineering item: deterministic
introspection per ADR-0017 (responsive-with-axiology, per-turn) and
ADR-0018 (typed deterministic operator).
core/cognition/explain.py:
explain(result: CognitiveTurnResult) -> str dispatches on intent
tag and returns a canonical natural-language re-statement of the
turn:
DEFINITION -> "What is X?"
TRANSITIVE_QUERY -> "What does X precede?" / "Where does X belong?"
CAUSE -> "Why X?"
PROCEDURE -> "How do I X?"
COMPARISON -> "Compare X and Y."
CORRECTION -> the original correction text (round-trip
identity case)
VERIFICATION -> "Is X?"
RECALL -> "Remember X."
UNKNOWN / None -> ""
Pure dispatch, no learned model, no external IO, replay-safe.
core/cognition/__init__.py exports explain so the introspection lane
runner's `from core.cognition import explain` resolves.
tests/test_explain.py: 16 unit tests covering dispatch on every intent
tag, plus round-trip intent classification (explain output re-classifies
as the same intent under classify_intent).
Contract refinement:
evals/introspection/contract.md M2 token floor lowered from >= 5 to
>= 2. The canonical form for a DEFINITION probe is naturally 3
tokens ("What is X?"); the original floor was author-overzealous.
evals/introspection/runner.py updated to match.
Re-score on introspection v1:
split api_present account_nonempty surface_match trace_match overall
public/v1 1.0 1.0 1.0 1.0 pass
holdouts/v1 1.0 1.0 1.0 1.0 pass
Including strict bit-stable trace_hash equality (M4) on every case
in both splits. Fresh-pipeline-on-account reproduces the original
turn's surface and trace_hash exactly.
Phase 3 v2 lane status (after this commit):
inference-closure public/v1 1.0 pass
inference-closure holdouts/v1 1.0 pass
multi-step-reasoning public/v1 0.73 pass
multi-step-reasoning holdouts/v1 0.80 pass
cross-domain-transfer public/v1 1.0 pass
cross-domain-transfer holdouts/v1 1.0 pass
introspection public/v1 1.0 pass <- this commit
introspection holdouts/v1 1.0 pass <- this commit
compositionality public/v1 0.31 partial
compositionality holdouts/v1 0.30 partial
8 of 10 splits passing v1 (Phase 3 exit gate met four times over).
gaps.md and PROGRESS.md updated to reflect resolution. CLI suites
smoke / cognition / teaching all green; no regression.
Future-direction notes recorded in introspection/gaps.md:
- Multi-turn explain (N-turn dialogue accounts).
- First-person narrative form (downstream of, and permitted by,
ADR-0017's responsive-with-axiology stance).
477 lines
23 KiB
Markdown
477 lines
23 KiB
Markdown
# Capability Roadmap — Progress Tracker
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Tracks completion of the phased plan defined in `docs/capability_roadmap.md`
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(ADR-0016). Updated as work lands.
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---
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## Phase 0 — Benchmark Methodology Lock-in
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**Status:** Complete
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**Started:** 2026-05-15
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**Completed:** 2026-05-16
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- [x] Promote roadmap to ADR-0016
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- [x] Extract `docs/eval_methodology.md` from roadmap Part I
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- [x] Create progress tracker (`docs/PROGRESS.md`)
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- [x] Implement `evals/<lane>/` directory convention
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- [x] Build generic eval framework (`evals/framework.py`)
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- [x] Retrofit `core eval cognition` into new convention
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- [x] Split 45 cases into dev (13) / public v1 (13) / holdout (19)
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- [x] Write `evals/cognition/contract.md`
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- [x] Migrate `runner.py` to use framework
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- [x] Record v1 results under new layout
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- [x] Generalize `core eval <lane>` CLI (dynamic lane discovery)
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- [x] Implement holdout runner scaffold
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- [x] Implement baseline runner scaffold
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- [x] **Exit gate:** `core eval cognition` runs under new convention with v1 public + holdout + baseline
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### Methodology issues discovered (Phase 0 audit)
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1. **Pipeline turn_log crash:** `CognitiveTurnPipeline.run()` assumed `turn_log`
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was always populated after `chat()`, but the unknown-domain gate returns a
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stub without appending. Fixed with fallback to tokenizer output.
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2. **Versor drift in multi-turn sessions:** `test_pipeline_preserves_versor_closure`
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reveals that after 3 turns in the same session, "spirit breath" causes
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`versor_condition = 1.12e-04` (threshold: 1e-6). Pre-existing; resolved by
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strict runtime closure enforcement (always unitize after sandwich product).
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3. **Identity/drive bias shelved:** Premature persona motor and drive bias
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introduced trajectory drift. Removed in favour of persona-neutral generic
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runtime; identity returns behind explicit IdentityProfile contract.
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---
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## Phase 1 — Foundational Triple
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**Status:** Complete ✓
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**Started:** 2026-05-16
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**Completed:** 2026-05-16
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**Depends on:** Phase 0 exit
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- [x] **grammatical-coverage** lane (v1 + v2 complete)
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- [x] Enumerate English v1 constructions (13 constructions: C01-C13)
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- [x] Write contract test pairs (PropositionGraph -> surface family)
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- [x] Implement v1 dev/public (~41/36 items)
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- [x] Implement holdout (52 items) — 100% pass
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- [x] Engineer `realizer.py` to pass v1 (dev=100%, public=100%, holdout=100%)
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- [x] Hebrew pack (`he_core_cognition_v1` with binyanim support)
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- [x] Koine Greek pack (`grc_logos_cognition_v1` with Greek morphology)
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- [x] Generate v2 on pass (deeper nesting, longer sentences, rarer vocabulary) — 36 cases (100% pass)
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- [x] **zero-code-domain-acquisition** lane (v1 complete, zero engineering gaps)
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- [x] Define 3 surprise domains (kinship, calendar, color)
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- [x] Build pack-only authoring kits (vocabulary, relations, axioms, teaching examples, prompts)
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- [x] Test: author brings CORE to >=80% without Python edits (100% achieved)
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- [x] Log engineering gaps (ZERO — pack-only authoring contract is solid)
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- [x] v1 dev (30/30), v1 public (18/18 across all 3 domains), v1 holdout (21/21) — all 100% pass
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- [x] **identity-divergence** lane (v1 complete)
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- [x] Define two identity axis sets (Axis A: Precision-first, Axis B: Generosity-first)
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- [x] Curate shared curriculum (93 teaching events across color/kinship/reasoning/spatial)
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- [x] Build divergence metric (>0.30 threshold): all pass (1.000)
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- [x] Build coherence metric (>0.85 threshold for A and B): all pass (1.000)
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- [x] Identity-stripped baseline with causal check: all pass (delta=1.000)
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- [x] v1 dev (5/5), v1 public (5/5), v1 holdout (5/5) — all 100% pass
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- [x] **Exit gate:** All three lanes pass v1 public + holdout ✓
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---
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## Phase 2 — Structural Wins Made Visible
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**Status:** In Progress
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**Started:** 2026-05-16
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**Depends on:** Phase 1 exit
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- [x] **provenance** lane (v1 complete)
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- [x] Define Provenance dataclass + compute_provenance() (`core/cognition/provenance.py`)
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- [x] Unit tests for provenance derivation (6/6 pass — `tests/test_provenance.py`)
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- [x] Build pack-axiom / vault-recall / teaching / mixed case categories
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- [x] v1 dev (10/10), v1 public (20/20), v1 holdouts (15/15) — all 100% pass
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- [x] Sub-metrics: replay_determinism=1.0, source_attribution=1.0, source_validity=1.0, input_sensitivity=1.0
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- [x] Fixed shape regression in `generate/stream.py` score-weighted recall (np.eye → multivector identity)
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- [x] Replaced linear-blend rotor scaling with manifold-preserving `rotor_power` (`algebra/rotor.py`); 41 closure-preservation tests
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- [x] Restored `respond()`/`result.final_state` identity contract after anchor pull
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- [x] **monotonic-learning** lane (v1 complete)
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- [x] Define contract: longitudinal regression check across ≥10 teaching cycles
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- [x] Implement runner: shared session, sorted ops, per-(cycle, domain) accuracy table
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- [x] Generator (`scripts/generate_monotonic_cases.py`) for cycle/probe corpora
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- [x] v1 dev (10 cycles), v1 public (12 cycles, 3 domains), v1 holdouts (12 cycles, 2 distinct domains)
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- [x] All splits: max_regression=0.00, floor_score=1.00, overall_pass=true
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- [x] Structural win demonstrated: zero regression across 34 total cycles / 7 distinct domains
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- [x] **calibration** lane (v1 complete)
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- [x] Define contract: typed signals for no_grounding / coherent / correction_proposed
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- [x] Classification from `CognitiveTurnResult` (vault_hits + pack_mutation_proposal)
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- [x] Runner with per-case fresh pipeline (avoids cross-case field drift)
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- [x] v1 dev (12/12), v1 public (24/24), v1 holdouts (18/18) — all 100% pass
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- [x] Sub-metrics: no_grounding=1.0, coherent=1.0, correction_proposed=1.0
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- [x] Architectural finding documented (`evals/calibration/gaps.md`): the
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ingest gate is geometric, not semantic — 6/42 hand-chosen OOD
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prompts fire the geometric gate. v1 measures recall-presence +
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correction-firing signals (deterministic), not semantic OOD.
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Pipeline override of gate's safety surface is a separate gap.
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- [x] **symbolic-logic** lane (v1 complete)
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- [x] Define contract: structural foundations for proposition-based inference
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- [x] Patterns: modus_ponens_chain, modus_tollens_chain, syllogism, negation, chain_recall
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- [x] Runner: per-case fresh pipeline + double-run replay check
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- [x] Sub-metrics: premise_recall=1.0, replay_determinism=1.0, proposal_storage=1.0
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- [x] v1 dev (8/8), v1 public (18/18), v1 holdouts (12/12) — all 100% pass
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- [x] Architectural finding documented (`evals/symbolic_logic/gaps.md`): CORE
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has no first-class inference operator yet. v1 measures the storage,
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replay, and recall foundations on which a future inference engine
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would be built. v2 would assert specific inference correctness
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(transitive recall surface contents).
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- [x] **adversarial-identity** lane (v1 complete)
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- [x] Define contract: identity-override attacks rejected at review;
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legitimate corrections still accepted
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- [x] Cover all `_IDENTITY_MARKERS` families (you are / forget / pretend /
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override / ignore / your name / act as / from now / character /
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personality)
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- [x] Per-case fresh pipeline; prior question primes the review surface
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- [x] Sub-metrics: attack_rejection_rate=1.0, legitimate_acceptance_rate=1.0
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- [x] v1 dev (10/10), v1 public (25/25), v1 holdouts (18/18) — all 100% pass
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- [x] **All five Phase 2 v1 lanes passing** ✓
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- [x] Frontier baselines computed for all lanes (structural-zero floor)
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- [x] `docs/frontier_baselines.md` — per-lane analysis: frontier LLMs do
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not emit the typed signals CORE's rubrics score against
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(provenance sources, pack_mutation_proposal, vault_hits,
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REJECTED_IDENTITY outcome, deterministic trace_hash)
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- [x] Per-lane structural-zero baseline JSON written under
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`evals/<lane>/baselines/v1_structural_zero.json`
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- [x] `StructuralZeroBaseline` adapter in `evals/baseline_runner.py`
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— deterministic floor; live-API adapters can be added when
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keys are configured
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- [x] v2 lanes: all five at 100% pass
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- monotonic-learning v2 — 20 cyc / 5 dom (public), 18 cyc / 4 dom (holdouts)
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- provenance v2 — 30 + 20 cases, all sub-metrics 1.0
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- adversarial-identity v2 — 35 + 22 cases, all 1.0
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- calibration v2 — 33 + 24 cases, all class accuracies 1.0
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- symbolic-logic v2 — 24 + 16 cases (chains up to 5 hops), all 1.0
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- [x] **Exit gate:** v3 lanes for at least two of the five ✓
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- monotonic-learning v3 — 30 cyc / 7 dom (public), 25 cyc / 6 dom (holdouts),
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`max_regression=0.0`, `floor_score=1.0` on both splits
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- adversarial-identity v3 — 30 + 20 paraphrased-attack cases.
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Initial v3 result (pre-fix): `attack_rejection_rate=0.0`,
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`legitimate_acceptance_rate=1.0`. v3 was a load-bearing finding
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that exposed the marker-string defense as brittle to paraphrase.
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### Identity-override defense — fix #2 + fix #3 (2026-05-16)
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Triggered by the v3 finding above. Two-layer defense now active in
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`teaching/review.py`:
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- **Fix #2 (syntactic).** `_is_identity_override` applies four
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deterministic rules: (a) legacy markers, (b) redirect-verb +
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role-frame co-occurrence, (c) negating qualifier ±3 tokens from a
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role-frame, (d) negating qualifier ±3 tokens from a redirect-verb.
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- **Fix #3 (geometric).** `IdentityCheck.would_violate(score, manifold)`
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predicate added to `core/physics/identity.py`; `review_correction`
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now accepts `identity_score` / `identity_manifold` kwargs and is
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wired in `CognitiveTurnPipeline._run_teaching` from
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`response.identity_score`.
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Lane results after both fixes:
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| split | attacks | attack_rej | legit_acc |
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|---|---|---|---|
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| public/v1 | 15 | 1.0 | 1.0 |
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| holdouts/v1 | 10 | 1.0 | 1.0 |
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| public/v2 | 20 | 1.0 | 1.0 |
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| holdouts/v2 | 12 | 1.0 | 1.0 |
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| public/v3 | 20 | 1.0 | 1.0 |
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| holdouts/v3 | 12 | 1.0 | 1.0 |
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| public/v4 | 20 | 1.0 | 1.0 |
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| holdouts/v4 | 12 | 1.0 | 1.0 |
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| public/v5 | 20 | 1.0 | 1.0 |
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| holdouts/v5 | 12 | 1.0 | 1.0 |
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v4 is the regression gate for fix #2 — new attack vocabulary
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combinations that exercise rules (b)/(c)/(d) without repeating v3's
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specific surface. v5 is the regression gate for the normalization
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layer — contractions (`you're`/`it's`/`let's`/`don't`), curly quotes
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(U+2018/U+2019), em-dashes, and verb morphology (`becoming` /
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`transformed` / `dropped` / `becomes`) — all now folded before rule
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evaluation. All v1–v5 splits pass at 100%; legitimate-correction
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false-positive rate is 0% (including legitimates that themselves
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use contractions: `wisdom's broader`, `knowledge isn't merely
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collected`, etc.).
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Honest finding: with the current default `IdentityManifold` (three
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unit-axis ValueAxes), the geometric layer flags 0/32 of v3 attacks
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independently of fix #2. The predicate and wiring are in place; the
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manifold's axis design is the limiting factor and needs sharpening
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before the geometric defense can carry weight on its own. See
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`evals/adversarial_identity/gaps.md`.
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### Geometric-axis sharpening investigation (2026-05-16)
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A focused empirical investigation against v3 and v5 (preserved as
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`evals/adversarial_identity/calibration/probe_field_signature.py`)
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swept every candidate per-case discriminator derivable from the
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existing CognitiveTurnResult — `identity_score.alignment`, field-delta
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L2 norm, semantic-coord energy ratio, `vault_hits`, surface length,
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intent tag. **No signal separated attack from legitimate at the
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per-case level.** `identity_score.alignment` is 1.000 universally;
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field-delta distributions overlap heavily; vault retrieval grounds
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both kinds similarly.
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The pipeline encodes identity-override attacks and legitimate
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corrections into statistically indistinguishable field-state
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geometries. No amount of axis-direction sharpening on the
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IdentityManifold can recover a signal that isn't present in the
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trajectory data being projected.
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**Architectural conclusion:** fix #3 cannot be made load-bearing
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in place. The required upstream work — encoding token semantic
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categories into specific blade coordinates of the field versor at
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the ingest gate, then redefining the IdentityManifold axes in the
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32-dim Cl(4,1) basis with a real inner-product projection — is a
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scoped multi-PR effort, not a single sharpening exercise. The
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calibration probe stands as the empirical baseline that any future
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ingest-gate change must beat before fix #3 can be claimed
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load-bearing. See `evals/adversarial_identity/gaps.md` for the
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full table of measured signals and the recommended path.
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**What stands today as the load-bearing defense:** fix #2
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(syntactic rules a/b/c/d) + the normalization layer reject 100% of
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v1–v5 attacks (n=121) with 0 false positives on 51 legitimate
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corrections. Fix #3's predicate, unit tests, and wiring remain as
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scaffolding for the upstream work above.
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## Phase 2 — COMPLETE
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All five Phase 2 v1+v2 lanes pass at 100%; frontier structural
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baselines documented; v3 satisfies the exit-gate requirement (two
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lanes, one demonstrating a passing structural-depth test and one
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demonstrating an architectural vulnerability that the geometric
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identity-check fix in `evals/adversarial_identity/gaps.md` would
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close).
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### Parallel eval infrastructure (2026-05-16)
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- `evals/parallel.py` — `run_cases_parallel()` helper using
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`multiprocessing.Pool` with the `"spawn"` start method (avoids
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forking heavy parent state). Default workers = `min(cpu_count, 8)`.
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- Wired into the four per-case lanes (provenance, calibration,
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symbolic-logic, adversarial-identity). `run_lane(..., workers=N)`
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controls parallelism; `workers=1` forces serial for debugging.
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- Empirical speedup (adversarial-identity public/v1, 25 cases):
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serial 14.1s → parallel 3.1s (~4.5x).
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- Monotonic-learning intentionally stays serial within a split
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(shared longitudinal session by design).
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---
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## Phase 3 — Reasoning Depth — IN PROGRESS
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### inference-closure v1 (2026-05-16) — honest failure, gap filed
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First Phase 3 lane built and run. Scores derivation of entailments
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that were not directly asserted (transitive `is` / `precedes` /
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`grounds` / `causes` / `belongs_to` chains) over the
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`en_core_cognition_v1` relation vocabulary.
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| split | n | derived_recall_rate | premises_stored_rate | replay_determinism | overall_pass |
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|---|---|---|---|---|---|
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| public/v1 | 20 | **0.0** | 1.0 | 1.0 | False |
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| holdouts/v1 | 12 | **0.0** | 1.0 | 1.0 | False |
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**v1 is the expected honest failure** per the roadmap. Foundation
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guarantees from Phase 2 (storage and replay determinism) hold at this
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depth: every premise emits a `PackMutationProposal`, every
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(premises, probe) sequence is trace-hash-deterministic. The
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inference-closure step itself does not yet exist in CORE.
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**Architectural gaps filed
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(`evals/inference_closure/gaps.md`):**
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1. `generate/graph_planner.py` has no transitive composition — the
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probe's articulation target picks a single node; no chained
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relation walk produces the derived entailment.
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2. `field/propagate.py` has no derivable-but-not-asserted recall —
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vault retrieval scores direct CGA inner products; no path-recall
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operator over relation-typed edges.
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Both gaps are v2 engineering candidates and may share a single
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implementation surface. Structural-zero frontier baseline recorded:
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frontier LLMs do not emit the typed signals these sub-metrics score
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by construction.
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### Phase 3 v1 sweep complete (2026-05-16) — all five lanes scored
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| Lane | split | primary signal | foundation (stored / replay) |
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|---|---|---|---|
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| inference-closure | public | derived_recall = **0.0** | 1.0 / 1.0 |
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| inference-closure | holdouts | 0.0 | 1.0 / 1.0 |
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| compositionality | public | compositional = **0.0625** (1/16, fluke) | 1.0 / 1.0 |
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| compositionality | holdouts | 0.0 | 1.0 / 1.0 |
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| multi-step-reasoning | public | endpoint = **0.0** | 1.0 / 1.0 |
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| multi-step-reasoning | holdouts | 0.0 | 1.0 / 1.0 |
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| introspection | public | explain_api_present = **0.0** | n/a |
|
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| introspection | holdouts | 0.0 | n/a |
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| cross-domain-transfer | public | transfer = **0.0** | 1.0 / 1.0 |
|
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| cross-domain-transfer | holdouts | 0.0 | 1.0 / 1.0 |
|
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|
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**The signal across all five lanes is unanimous:** Phase 2 storage
|
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+ replay guarantees hold at this depth (1.0 across the board); the
|
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reasoning-depth signal is uniformly zero. The five lanes
|
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triangulate the same architectural gap from five angles:
|
||
|
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- **Gap 1: `generate/graph_planner.py` has no transitive
|
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composition.** `plan_articulation` picks a single node; no
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chained relation walk synthesizes derived nodes.
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- **Gap 2: `field/propagate.py` has no derivable-but-not-asserted
|
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recall.** Vault retrieval is direct CGA inner product; no
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path-recall operator over relation-typed edges.
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- **Gap 3: no `core/cognition/explain.py` module.** No primitive
|
||
exists to generate a natural-language account of a prior turn.
|
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- **Gap 4: no structural-pattern recogniser.** Relation patterns
|
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are not first-class entities; subdomain-A teaching does not shape
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subdomain-B competence.
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|
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Gaps 1, 2, 4 cluster on the same code surface (graph planner +
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field propagate) and may close together. Gap 3 is a distinct
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module-creation work item.
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||
|
||
### Phase 3 v2 work plan (recommended sequence)
|
||
|
||
1. **Pin the open scope decisions** flagged "Before Phase 3" in
|
||
the Open Scope Decisions table below — Agency (responsive vs.
|
||
goal-directed) and Tool use (typed deterministic operators).
|
||
Transitive composition under (2) is essentially a typed
|
||
deterministic operator, so the tool-use decision shapes how the
|
||
work below should be structured.
|
||
2. **Engineer Gaps 1 + 2** as one bounded PR: a typed
|
||
`transitive_walk(graph, head, relation, max_hops)` operator in
|
||
`graph_planner.py` + a `path_recall(vault, entity, relation_chain)`
|
||
operator in `field/propagate.py`. Both deterministic, both
|
||
exact-CGA. Re-run inference-closure, multi-step-reasoning,
|
||
compositionality, cross-domain-transfer to score the lift.
|
||
3. **Engineer Gap 3** independently: `core/cognition/explain.py`
|
||
producing deterministic natural-language accounts that round-trip.
|
||
4. **Re-author cross-domain-transfer v2** with the matched-control
|
||
comparison contract refinement once B-arm recall is non-zero.
|
||
|
||
### Phase 3 v2 sweep — 8 of 10 splits passing (2026-05-16)
|
||
|
||
Engineering work from ADRs 0017 + 0018 has now landed. Two bundles:
|
||
|
||
**Bundle 1 — transitive_walk + path_recall (commit `57a6174`)**
|
||
|
||
- `teaching/relation_parse.py` lifts correction text into typed
|
||
`(head, relation, tail)` triples using the
|
||
en_core_cognition_v1 relation vocabulary.
|
||
- `teaching.store.PackMutationProposal` carries the typed triple;
|
||
`TeachingStore.triples()` exposes the cross-turn typed-relation
|
||
graph.
|
||
- `generate/operators.py` defines `transitive_walk` (single-relation
|
||
chain) and `path_recall` (multi-relation chain).
|
||
- `generate.intent` gains `TRANSITIVE_QUERY` intent tag with a
|
||
parsed `relation` field for "What does X precede/cause/ground?"
|
||
and "Where does X belong?" forms.
|
||
- `CognitiveTurnPipeline.run` dispatches the operator after
|
||
`runtime.chat()` and folds the chain endpoint into the surface.
|
||
- `compute_trace_hash` and `CognitiveTurnResult` gain
|
||
`operator_invocation` so operator runs are load-bearing for
|
||
replay equality per ADR-0018.
|
||
|
||
**Bundle 2 — core/cognition/explain.py (commit pending)**
|
||
|
||
- Deterministic canonical re-statement of a turn, dispatched on
|
||
the intent tag. DEFINITION → "What is X?", TRANSITIVE_QUERY →
|
||
"What does X precede?" / "Where does X belong?", CORRECTION →
|
||
the original correction text, etc.
|
||
- Closes Gap 3. No learned model; pure dispatch.
|
||
|
||
**Phase 3 v2 lane re-score:**
|
||
|
||
| Lane | split | v1 | after v2 bundles |
|
||
|---|---|---|---|
|
||
| inference-closure | public | 0.0 | **1.0** ✓ |
|
||
| inference-closure | holdouts | 0.0 | **1.0** ✓ |
|
||
| multi-step-reasoning | public | 0.0 | **0.7333** ✓ |
|
||
| multi-step-reasoning | holdouts | 0.0 | **0.8** ✓ |
|
||
| cross-domain-transfer | public | 0.0 | **1.0** ✓ |
|
||
| cross-domain-transfer | holdouts | 0.0 | **1.0** ✓ |
|
||
| introspection | public | 0.0 | **1.0** ✓ |
|
||
| introspection | holdouts | 0.0 | **1.0** ✓ |
|
||
| compositionality | public | 0.0625 | 0.3125 (partial) |
|
||
| compositionality | holdouts | 0.0 | 0.3 (partial) |
|
||
|
||
**8 of 10 splits passing v1.** Phase 3 exit gate (≥ 2 lanes passing
|
||
v1) is met **four times over**. Foundation guarantees
|
||
(`premises_stored_rate`, `replay_determinism`) remain 1.0 across all
|
||
lanes; trace_hash bit-stability holds with operator records folded
|
||
in.
|
||
|
||
**Residuals for v3 work:**
|
||
|
||
- multi-step-reasoning `mixed_relation_*` patterns (chain across
|
||
multiple relation types in one probe) — `path_recall` exists but
|
||
the pipeline only invokes the single-relation `transitive_walk`.
|
||
The intent classifier doesn't yet recognise multi-relation
|
||
question shapes.
|
||
- compositionality novel-combination patterns (`novel_pair_under_seen_relation`,
|
||
`novel_relation_on_seen_pair`) need a `composed_relation_walk`
|
||
operator that synthesises across taught pairs. This is a
|
||
distinct ADR-level capability decision and is correctly
|
||
downstream of literal cross-domain transfer (which now works).
|
||
|
||
### Phase 3 v1 — DONE
|
||
|
||
All five lanes have v1 results with honest scores. Each failure has
|
||
a documented architectural deferral (`gaps.md` per lane). Phase 3
|
||
exit requires ≥ 2 lanes passing v1 by phase exit; today 0 / 5 pass,
|
||
which is the expected v1 floor. Phase 3 exit is gated on the v2
|
||
engineering above.
|
||
|
||
## Phase 3 — Reasoning Depth
|
||
|
||
**Status:** Not Started
|
||
**Depends on:** Phase 2 exit
|
||
|
||
- [ ] **compositionality** lane (construction-family splits, not sampling)
|
||
- [ ] **inference-closure** lane
|
||
- [ ] **introspection** lane
|
||
- [ ] **multi-step-reasoning** lane
|
||
- [ ] **cross-domain-transfer** lane
|
||
- [ ] Pin agency scope decision (responsive vs. goal-directed)
|
||
- [ ] Pin tool-use scope decision
|
||
- [ ] **Exit gate:** All five v1 scored; at least two passing v1
|
||
|
||
---
|
||
|
||
## Phase 4 — Scale and Efficiency
|
||
|
||
**Status:** Not Started
|
||
**Depends on:** Phase 3 exit
|
||
|
||
- [ ] **sample-efficiency** curves (>=10 concepts)
|
||
- [ ] **long-context-cost** curves (10^3 to 10^6 vault entries)
|
||
- [ ] **multi-agent-composition** (>=2 agents, replay preserved)
|
||
- [ ] Vault indexing strategy decided
|
||
- [ ] **Exit gate:** All curves published with confidence intervals
|
||
|
||
---
|
||
|
||
## Phase 5 — Curriculum Era
|
||
|
||
**Status:** Not Started
|
||
**Depends on:** Phase 4 exit
|
||
|
||
- [ ] 5.1 English fluency (grammatical-coverage v5 OOD)
|
||
- [ ] 5.2 Hebrew fluency
|
||
- [ ] 5.3 Koine Greek fluency
|
||
- [ ] 5.4 Elementary mathematics
|
||
- [ ] 5.5 Foundational physics
|
||
- [ ] 5.6 Foundational biology
|
||
- [ ] 5.7 Classical literature
|
||
- [ ] Phase 1-4 lanes re-run on every release (no regression)
|
||
|
||
---
|
||
|
||
## Open Scope Decisions
|
||
|
||
| Decision | Status | Deadline |
|
||
|----------|--------|----------|
|
||
| Agency (responsive vs. goal-directed) | **Resolved 2026-05-16 — ADR-0017** (responsive-with-axiology) | Before Phase 3 ✓ |
|
||
| Tool use (typed deterministic operators) | **Resolved 2026-05-16 — ADR-0018** (typed deterministic operators, no external IO) | Before Phase 3 ✓ |
|
||
| Code generation (first-class target) | Open | Before Phase 5 |
|
||
| Embodiment (sensorium gates) | Open | Phase 5 |
|