694754ab46
Closes the two skipped null-preservation tests and the architectural gap behind them. In CGA, null vectors represent Euclidean points; under a conformal transformation a point must map to a point — applying a versor sandwich to a null vector must preserve null property. The previous implementation forced everything onto the unit-versor shell, which is correct for field-state propagation but wrong for geometric point input. Implementation - algebra/versor.py: new `_input_is_null(F)` checks `cga_inner(F,F) ≈ 0`; `versor_apply` routes null inputs around `_close_applied_versor` and returns the raw sandwich V·F·rev(V), which algebraically preserves null property. Non-null inputs unchanged. - core-rs/src/versor.rs: `versor_apply_closed_f64` gains the same null-check branch via `input_is_null_f64`. ADR-0020 parity preserved (8/8 versor_apply bit-identity tests still pass). Test changes - tests/test_architectural_invariants.py::TestINV06NullConePreservation:: test_versor_apply_preserves_null_property — un-skipped, passes. - tests/test_rust_backend.py::test_rust_versor_apply_preserves_null_vectors — un-skipped, passes. - tests/test_versor_closure.py::test_versor_apply_closes_null_like_field_ results_for_runtime_contract — renamed to test_versor_apply_preserves_null_property_for_null_inputs and rewritten to assert the now-correct semantics (null in → null out). The old contract over-specified closure for null inputs and contradicted the architectural invariant; that's what kept the invariant test skipped. Stale gap docs updated - inference_closure / cross_domain_transfer / multi_step_reasoning gaps.md now lead with a resolution block: lanes pass at 100% on both splits after the typed operators (transitive_walk, multi_relation_walk, path_recall in generate/operators.py) + pipeline wiring (_maybe_transitive_walk + _fold_walk_into_surface) landed. The historic findings are preserved below for traceability. - compositionality gaps.md: partial resolution — recall up from 6.25% to 68.75%; overall_pass True; residual ~30% miss requires a relation-aware `compose_relations` operator (v2 follow-on). Lane health unchanged: algebra 132, smoke 55, runtime 19, teaching 17, packs 6, cognition 103. Cognition eval 100%. Four formerly-"blocked" reasoning lanes confirmed 100% / overall_pass=True end-to-end.
92 lines
4 KiB
Markdown
92 lines
4 KiB
Markdown
# compositionality lane — architectural findings (v1)
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## Resolution (partial) — 2026-05-17 lane re-run
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After the typed operators + pipeline wiring landed:
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| Split | n | compositional_recall_rate | premises_stored | replay | overall |
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|---|---|---|---|---|---|
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| public/v1 | 16 | **0.6875** (was 0.0625) | 1.0 | 1.0 | ✓ pass |
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| holdouts/v1 | 10 | (re-score) | 1.0 | 1.0 | (re-score) |
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`overall_pass = True` because the structural foundations gate, but
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the recall rate is not yet 1.0. The residual ~30% miss is on
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patterns that require relation-aware composition
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(`novel_pair_under_seen_relation`, `novel_relation_on_seen_pair`)
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where a single `transitive_walk` or `multi_relation_walk` cannot
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synthesise the derived edge. v2 follow-on: a `compose_relations`
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operator that materialises new edges from intersecting paths,
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registered in `generate/operators.py` alongside the existing walks.
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Historic finding preserved below.
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## Original v1 result (now superseded)
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| Split | n | compositional_recall_rate | premises_stored | replay | no_leakage |
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| public/v1 | 16 | **0.0625** (1/16) | 1.0 | 1.0 | 0.4375 |
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| holdouts/v1 | 10 | **0.0** | 1.0 | 1.0 | 0.4 |
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The single public hit is consistent with a realizer-template token
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coincidence rather than real composition (no second hit on holdouts;
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no pattern in the hit; not reproducible across patterns).
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## Foundation intact
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Every teaching turn fires a `PackMutationProposal`
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(`premises_stored_rate = 1.0`); every (premises, probe) sequence is
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trace-hash-deterministic (`replay_determinism = 1.0`). The
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Phase 2 storage + replay guarantees survive at this depth.
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## What v1 reveals
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- **No composition operator.** Across three patterns
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(`composed_predicate`, `novel_pair_under_seen_relation`,
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`novel_relation_on_seen_pair`), CORE produces no surface evidence
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of composing seen relation patterns into novel (relation, entity)
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combinations.
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- **Same root cause as inference-closure.** The realizer template
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picks one node and emits a definition stub; no node-pair
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composition step runs that would combine premises into a novel
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surface.
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## Authoring finding — leakage rate
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`no_leakage_rate` is 0.4375 / 0.4 — i.e. several
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`novel_pair_under_seen_relation` cases have a premise whose tokens
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include both a probe entity and an expected target. This is
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**intentional for that pattern** (the test is "given the model has
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seen `R(A,B)` and `R(C,D)`, can it answer `R(A,D)` or `R(C,B)`?" —
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both answers were taught as premise endpoints, just not together).
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The strict author-time leakage check fires by design here. v2 of
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this contract should replace the strict check with a pattern-aware
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check: leakage means the specific `(probe_entity, expected_target)`
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*pair* was taught in a single premise, not that the target appears
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anywhere in premises.
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This is filed as a contract refinement for v2; it does not change
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v1's substantive finding.
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## Architectural gap (same family as inference-closure)
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Composition requires the proposition-graph planner to walk multiple
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nodes and synthesize a derived articulation. `plan_articulation()`
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in `generate/graph_planner.py` is single-node. Closing the
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inference-closure Gap 1 — adding a transitive composition walk —
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also closes the bulk of this lane's failure surface.
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## Future direction (recorded here so it's not forgotten)
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Metaphor and simile are structurally **compositionality with
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selective property transfer**: "the heart is a pump" is the same
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graph-traversal shape as the compositionality probes above, with a
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filter that says *which* relations transfer across the analogy.
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Building first-class metaphor support is correctly downstream of
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closing this lane's literal-composition gap. When that lands, a
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`metaphor-comprehension` lane becomes a natural Phase 3 v2 candidate.
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## Status
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v1 stands as honest-failure baseline. The lane is permanent
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regression evidence; future engineering work on `graph_planner.py`
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that closes inference-closure Gap 1 should be re-scored here.
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