Zero behavior delta on the main baseline (both substrates produce
0/50 admission today) — but every subsequent ADR-0131.G.<n> iteration
now produces attributable admission deltas on the probe, instead of
silently extending a parser layer the probe wasn't measuring.
Background: ADR-0131.G's probe consulted run_lane → _score_one →
parse_problem (legacy first-match-wins parser, pre-ADR-0126). Every
G.<n> iteration extends the candidate-graph parser via
_score_one_candidate_graph → parse_and_solve. The mismatch was
discovered during G.3 development and explicitly reserved as this
follow-up.
Changes:
- run_coverage_probe.py: switch import to _score_one_candidate_graph;
new private _score_lane aggregator mirrors run_lane's output shape
via per-case scoring; report root adds "substrate": "candidate_graph"
for audit trail.
- train_sample_coverage_report.json: regenerated. All metrics
byte-identical to prior baseline (0/50 admission, wrong=0).
refused_reasons_top text differs (candidate_graph: prefix instead
of parser:) — expected and part of the substrate audit-trail shift.
Discipline: separate small PR per ADR-0131.G's "expansion that only
moves admission must be a standalone PR" principle. Substrate swap
attributable; future G.<n> deltas attributable.
Evidence:
- python3 -m evals.gsm8k_math.train_sample.v1.run_coverage_probe
→ admission 0/50, wrong=0, safety_rail_intact=True, exit 0
- pytest tests/test_adr_0131_G_gsm8k_coverage_probe.py
→ 8/8 pass in 0.18s (no test edits needed; tests pin invariants
not numbers)
- No changes to runner.py, no changes to any G.<n> work in flight.
Effect on in-flight iterations: each G.<n> PR (G.1 Gemini / G.2 #182 /
G.3 #183 / G.4 Opus#2) rebases after this lands and refreshes its
committed train_sample_coverage_report.json with the new substrate's
numbers. Rebase is mechanical.
First capability-axis iteration after ADR-0131.G baseline. Extends the
candidate-graph parser's <value> slot to recognize:
- Money symbol literals: $N and $N.NN (1-2 decimals); $N.NNN refused
- Money word forms: N dollars / N cents
- Hyphenated multi-word cardinals: twenty-five, ninety-nine, ...
All money values normalize to integer cents, unit 'cents' — pack-aligned
with en_units_v1's canonical_unit='cent' for the money dimension.
en_numerics_v1's parse_compound_cardinal handles hyphenated cardinals.
Parser changes (generate/):
- math_candidate_parser.py: _VALUE alternation widened; _resolve_value
refactored to return _ResolvedValue|None carrying optional unit
override; _INITIAL_HAS_RE unit slot made optional; dollar/dollars →
cents normalization at candidate build.
- math_roundtrip.py: new _unit_grounds helper (money-aware); _value_grounds
widened for the three new literal shapes; roundtrip_admissible uses
_unit_grounds for the unit check.
- math_candidate_graph.py: _initial_admissible and _question_admissible
use _unit_grounds.
New axis lane (evals/math_capability_axes/G3_numerics/v1/):
- 26 curated cases (20 positive across 4 classes + 6 refusal probes)
- runner.py wraps _score_one_candidate_graph; byte-equal report.json
- 20/20 positive solved correct; 6/6 refusal probes refused typed;
solved_wrong == 0; overall_pass == True
Tests: 27/27 in 0.19s. 420 existing candidate-parser/math-parser/pack
tests still green. GSM8K probe safety rail (admitted_wrong == 0)
preserved.
Honest scope-limit (documented in ADR): admission_rate on the GSM8K
probe stays at 0/50 because (a) the probe currently consults the legacy
parser path, not the candidate-graph pipeline G.3 extends, and (b) most
money-bearing GSM8K cases fail first on verb (G.1) or multi-clause (G.4)
shape, not on the money literal. The axis lane is the load-bearing
measurement for this iteration. Reserved follow-up: a small probe-
infra ADR to switch run_coverage_probe.py to the candidate-graph
pipeline.
Out of scope, deferred to G.3.1: fractions end-to-end (resolver supports
N/M but no axis cases), multi-currency (¢ € £ ¥ ₱), space-separated
multi-word cardinals (one hundred), word-number-adjective compositions
(five full boxes).
Wire compare_additive / compare_multiplicative extractors into the
candidate-emitting sentence parser, closing the deferred phase flagged
at generate/math_candidate_parser.py:30.
Capability axis: comparatives (additive + multiplicative)
- generate/math_candidate_parser.py: new _compare_additive_candidates,
_compare_multiplicative_candidates, _compare_nested_candidates
emitting CandidateOperation records keyed to the four
Comparison.direction literals registered in ADR-0123.
- Closed-set anchor alternation; 'less' admitted as surface synonym of
'fewer'; reference slot widened to admit "the number/amount of <unit>"
for nested forms.
- Nested 'A has N more <unit> than M times <REF>' emits two flat
candidates (additive + multiplicative); binding-graph picks the
admissible composition or refuses (no solver stub).
Curated axis lane (24 cases)
- evals/math_capability_axes/G2_comparatives/v1/cases.jsonl:
8 additive / 8 multiplicative / 3 nested / 5 refusal
- evals/math_capability_axes/G2_comparatives/v1/runner.py +
report.json: deterministic, wrong==0 gate, byte-equal across runs.
Tests (21 new)
- tests/test_adr_0131_G2_comparatives.py: per-direction at-least-one
passing, nested-both-emitted, closed-set refusal, runner
byte-equality, GSM8K-probe gate (comparative-clause refusals
strictly decrease).
GSM8K-probe gate (chosen: comparative-clause refusals ↓)
- evals/gsm8k_math/train_sample/v1/report.json (candidate-graph
probe): comparative-clause refusal count 2 → 1 (case 0009 'Jen has
10 more ducks than four times the number of chickens' moves from
statement-clause refusal to question-layer refusal). admitted_wrong
remains 0; admission_rate unchanged (downstream composition is a
follow-up ADR).
- evals/gsm8k_math/train_sample/v1/train_sample_coverage_report.json
(legacy probe): refreshed, byte-identical (legacy parser untouched).
B3 + candidate-graph + GSM8K probe lanes all pass (90/90). Direction
vocab stays closed to {more, fewer, times, fraction}; wrong==0
preserved everywhere.
ADR-0131 deferred GSM8K because it rewards paraphrase flexibility,
which is the deterministic engine's structural weakness. This ADR
re-engages it on architecture-aligned terms: as a *coverage probe*
of the bounded grammar + binding graph, not a promotion gate.
The framing pinned by this ADR:
GSM8K is not a target. The model's capability is the target.
GSM8K passing is the symptom of capability, not the goal of
the work.
Wrong mindset (rejected by ADR's iteration discipline):
"Find templates that admit more GSM8K cases."
Right mindset (load-bearing):
"Extend the model's NL-to-typed-graph capability along
principled axes (verb classes, comparative structures, numeric
forms, multi-clause grammar). GSM8K admission rises as a
side effect alongside every other word-problem corpus."
Baseline pinned by this commit:
admission_rate: 0/50 = 0.0%
admitted_wrong: 0 (gate intact, safety rail bulletproof)
refused: 50/50 = 100.0%
Every refusal is a typed parser error citing the specific clause
that did not match a template. Zero crashes, zero confabulations
— refusal-first works perfectly at admission rate zero.
What's in this PR:
- ``docs/decisions/ADR-0131.G-gsm8k-coverage-probe.md``: the ADR.
Cites parents (ADR-0131, -0115/-0116/-0117, -0131.3, -0132..-0135).
Documents the capability-first iteration discipline that every
subsequent ADR-0131.G.<n> must follow:
1. Name a single capability axis the iteration extends
2. Add B3-style curated coverage cases (capability proves
itself OUTSIDE GSM8K)
3. Re-run both B3 lane + GSM8K probe; B3 must not regress
4. Reject any expansion that only moves GSM8K admission
- ``evals/gsm8k_math/train_sample/v1/run_coverage_probe.py``:
pure-adapter wrapper around the existing run_lane. Emits a
deterministic train_sample_coverage_report.json with metrics,
per-case outcomes, and the top refused-reason families (the
work queue for capability extension).
- ``evals/gsm8k_math/train_sample/v1/train_sample_coverage_report.json``:
the baseline report. Diff-able artifact every future iteration
moves.
- ``tests/test_adr_0131_G_gsm8k_coverage_probe.py``: 8 contract
tests pinning the safety rail (admitted_wrong == 0), typed
refusal invariant (every refused case has non-empty reason),
closed outcome vocabulary, deterministic replay, committed-
report matches fresh-run.
The promotion-gate composite (B1 + B2 + B3) is unaffected.
ADR-0131.4 still consumes those three. The GSM8K probe is
empirical context for honest external claims, not a gate.
* feat(ADR-0131.1.F): frontier-baseline comparison harness for B1
Adapts the ADR-0119.4 methodology (frozen citations + comparison JSON
with disclaimer) to B1, with three additions for the
architecture-aligned claim:
1. A provider-agnostic live head-to-head runner. Adapters for
Anthropic / OpenAI / Google import their SDKs lazily so the
package loads cleanly without them installed. Each provider has a
documented FRONTIER_<VENDOR>_KEY env var; the runner refuses with
a typed FrontierRunError when keys are absent and the cache cannot
cover all cases. Every response is cached one-record-per-line at
responses/<provider>/<model>.jsonl so subsequent runs replay
byte-equally without re-calling the API.
2. A conservative free-text-to-closed-vocab verdict parser. Ambiguous
or sentinel-free provider replies collapse to "refused" — a
polarized verdict is never confabulated from prose. Chain-of-
thought replies use last-token-wins (provider deliberates, then
concludes). This is the load-bearing seam that prevents the
runner from manufacturing scores the provider didn't deliver.
3. Architecture-aligned comparison metrics. accuracy is reported but
foregrounded as the least-load-bearing; refusal_correctness
(CORE 100% by lane-gate construction vs. frontier confabulation
rate) and determinism (CORE byte-equal vs. frontier variance) are
the differentiators.
Frozen adjacent-benchmark citations cover Anthropic
(claude-3-5-sonnet on MATH, claude-opus-4-1 on AIME), OpenAI
(gpt-4o on MATH), and Google (gemini-1.5-pro on MATH). The scope
disclaimer documents that these are adjacent, not head-to-head.
Head-to-head numbers, when run, land in the cache; the comparison
JSON joins them with CORE's existing lane result.
22 tests pin the methodology: citation shape (every field, https
URL, YYYY-MM-DD date), provider-registry shape, verdict-parser
conservatism (multiple chain-of-thought cases), runner caching
behavior (no double-invoke), comparison-JSON determinism (byte-equal
across runs).
No live API call at test time. The harness gates real runs behind
explicit env vars + CLI invocation.
Composes with ADR-0131.1 (B1 v1), ADR-0131.1.B (v1.B hardening,
#169), ADR-0131.1.S (sealed holdout, #173).
* feat(ADR-0131.1.F): live head-to-head — anthropic/claude-sonnet-4-6
First real frontier baseline on the full B1.B 185-case set
(curated + generated). Cached one-record-per-line at
responses/anthropic/claude-sonnet-4-6.jsonl. Re-runs replay from
disk; no further API calls.
Headline (after scoring fix):
CORE 185/185 = 100.0% accuracy
3/3 = 100.0% refusal_correctness
deterministic (byte-equal across runs)
anthropic/claude-sonnet-4-6 182/185 = 98.4% accuracy
1/3 = 33.3% refusal_correctness
non-deterministic (temperature=0, but
not byte-equal architecturally)
The 1.6pp accuracy gap is informative; the refusal-correctness gap
is the architecture-aligned story. Sonnet's three misses:
sym-eq-v1-0016 [difference_of_squares]
(x^2 + 1)*(x^2 - 1) vs x^4 - 1
Sonnet: NOT_EQUIVALENT (math error on a textbook identity)
sym-eq-gen-v1-0153 [generated_refusal_function]
sin(x) vs x
Sonnet: NOT_EQUIVALENT (confabulated — should refuse,
transcendental outside polynomial scope)
sym-eq-gen-v1-0154 [generated_refusal_negative_exponent]
x^-1 vs 1
Sonnet: NOT_EQUIVALENT (confabulated — should refuse,
negative exponent outside scope)
Sonnet correctly refused only on syntactically malformed input
("x +"); on syntactically-valid-but-semantically-out-of-scope inputs
it confidently polarized rather than refusing. CORE refuses both
classes with typed reasons.
Scoring fix: comparison.py now composes curated + generated cases
(mirroring runner.py) so the head-to-head scores the full 185-case
lane, not just the 30 curated. The initial run scored only 30/185
because the generated set was not loaded into _load_cases().
22/22 frontier-methodology tests still pass.
* feat(ADR-0131.1.F): three more head-to-head runs + Ollama adapter
Three additional providers ran against the full B1.B 185-case set,
joining the prior claude-sonnet-4-6 result:
CORE 185/185 = 100.0% acc | 3/3 = 100% refusal | 33 ms
claude-sonnet-4-6 182/185 = 98.4% acc | 1/3 = 33.3% refusal | 294 s
claude-opus-4-7 178/185 = 96.2% acc | 1/3 = 33.3% refusal | 309 s
gpt-5 134/185 = 72.4% acc | 1/3 = 33.3% refusal | 1153 s
qwen3:8b (M1 local, partial) 91/91 = 100.0% acc | n/a no refusal-class | killed
CORE is the only system at 100% on both axes, and runs ~9,000×
faster than the cheapest cloud frontier, ~35,000× faster than gpt-5,
and finishes in less wall time than a single API call to any of the
three frontier models.
Three distinct frontier brittleness modes, all rooted in
"not actually canonicalizing":
- sonnet-4-6 confabulates polarized verdicts on out-of-scope
inputs (sin(x), x^-1). Misses one in-scope difference-of-squares
identity (x^2+1)*(x^2-1) vs x^4-1.
- opus-4-7 pattern-shortcuts five near-miss-constant cases —
accepts (-x+3)*(4x+1) == -4x^2+11x+4 (correct constant is 3,
not 4) without expanding. Same two out-of-scope confabulations
as sonnet.
- gpt-5 over-refuses 50 in-scope cases — literally replies
"REFUSED" to x*(x+1) == x^2+x and (x+1)*(x-1) == x^2-1. Same
two out-of-scope confabulations as sonnet/opus.
The qwen3:8b partial is the surprise: on the 91 in-scope cases it
completed (spanning the categories where the frontier models failed),
it scored 100%. Refusal-class cases weren't reached before the run
was killed for being impractically slow (~22s/case on M1).
Changes in this commit:
- frontier_runner.py: anthropic adapter now omits ``temperature``
for claude-opus-4-x (the parameter is rejected by 4.x models);
openai adapter switches to ``max_completion_tokens`` for the
gpt-5 / o-series reasoning models; new ``_ollama_invoke`` that
posts to localhost:11434 with no third-party dep; per-case
``latency_ms`` is now captured on every NEW cached response
(future runs only — these four runs pre-date the patch).
- comparison.py: ``_load_cases`` composes curated + generated
(185 cases) instead of curated only; ``_score_provider``
surfaces ``latency_summary`` when records carry latency_ms.
- tests: provider-registry test relaxed to "cloud trio is a
subset of PROVIDERS"; env-key test allows ``_KEY`` (cloud
secret) or ``_URL`` (local endpoint).
Refines BoundUnknown from "the symbol whose value the solver determines"
to "the symbol at a specific temporal/state index with a specific
question-form". Two new required fields on BoundUnknown — state_index
(initial/terminal/Operation(operation_index)) and question_form
(count/rate/total/difference/ratio/identity) — populated by the new
pure-function resolver in generate/binding_graph/question_target.py.
The adapter (ADR-0133) now delegates Unknown -> BoundUnknown construction
to bound_unknown_from_math_problem_graph. No runtime wiring, no solver
invocation. Phase 5 (bounded-grammar / B3 integration) remains deferred.
Refusal-first via the new QuestionTargetError (sibling of AdapterError /
AdmissibilityError). Closed reason vocab: not_a_math_problem_graph,
unknown_entity_not_in_entities, apply_rate_unit_mismatch,
unmappable_question_form. Closed precedence rule on question_form
documented in ADR-0135 (compare_multiplicative > compare_additive >
apply_rate{numerator|denominator unit-match} > count); ambiguity refuses.
SemanticSymbolicBindingGraph.__post_init__ gains a cross-collection
guard: Operation(operation_index) must satisfy operation_index <
len(equations). canonical_string emission widened to include
state=... form=... tokens (hash differs from Phase 3 main by design —
not a regression; byte-equal across runs preserved).
Parents: ADR-0132 / ADR-0133 / ADR-0134.
Tests: +70 new (45 unit in test_binding_graph_question_target.py +
25 integration in test_binding_graph_adapter_question_target.py); 5
Phase 1+3 BoundUnknown fixtures migrated. Total binding-graph lane
295/1 pass (1 pre-existing test_symbol_binding_uses_slots failure on
Python 3.14, unrelated to Phase 4 — exists on origin/main). Pyright
clean on new and modified files. No edits to algebra/, chat/, core/,
or runtime hot path. Field invariant untouched.
Wires deterministic, refusal-first dimensional analysis into the
binding-graph adapter. Every BoundEquation emitted by
bind_math_problem_graph now carries either admissibility_status='admitted'
+ populated unit_proof or admissibility_status='refused' + typed
refusal_reason. No silent coercion; no invented units; no solver.
Adds:
- generate/binding_graph/units.py — pure unit algebra over a 6-dim
integer exponent vector (length, time, mass, money, count,
temperature). Closed vocabulary loaded once from en_units_v1
(ADR-0127) and memoized; composite "<num>_per_<denom>" resolved
recursively; conservative depluralization; refusal-first.
- generate/binding_graph/admissibility.py — check_admissibility with
per-operation-kind dispatch over the closed 8-string vocab, typed
AdmissibilityError (closed reason set), frozen UnitProof.
- ADR-0134 documenting the contract, invariants, and Phase 4-5
deferrals.
Adapter changes are surgical: synthesizes operand-literal symbols where
the verifier needs them (op<NNN>__multiplicand / __divisor / __rate),
then stamps each equation via check_admissibility. Input/output types
unchanged; bind_math_problem_graph still byte-equal across runs.
Tests: 226 total in the binding-graph lane (110 Phase 1+2 still pass; 47
units + 40 admissibility + 29 adapter-units new). Pyright clean on all
new files. No runtime wiring outside generate/binding_graph/.
Phase 4 (question-target binding) and Phase 5 (B3 / bounded grammar)
remain deferred per the brief.
Tests on main had drifted from intentional substrate changes that
weren't propagated to their fixtures or pinned values. Categories:
1. PackMutationProposal missing source= arg (3 tests across
test_mutation_proposal_type, test_provenance, test_expert_demo_runnable):
add ProposalSource(kind="operator", source_id="", emitted_at_revision="test")
to the shared fixture. test_expert_demo_runnable also retargets the
"unpromoted domain" example from systems_software (now promoted) to
arithmetic (real but unpromoted).
2. Pack content grew (test_en_core_meta_v1_pack 73→77 entries, 49→53 verbs;
test_en_core_spatial_v1_pack 24→25 entries adding "places" plural surface):
bump expected counts; allow new provenance shapes from the
adr-0085-style-v2 review (including the seed:core_meta/seed:core_spatial
author-time typos on two entries each — documented inline rather than
masked).
3. Registry self-documenting "add names to the set" failures
(test_lane_sha_verifier: add curriculum_loop_closure;
test_register_runtime_threading: add gloss_aware_cause_surface,
pack_grounded_unknown_surface, teaching_grounded_surface_transitive).
4. Gloss content was seeded where tests pinned None
(test_pack_resolver_glosses TestMissingGlossesIsBackCompat): switch
the no-glosses pack from en_core_relations_v1 (since glossed) to
en_minimal_v1 (still gloss-free); narrow resolve_gloss probe to that
pack so other packs' glosses can't shadow.
5. Entry-id renumber from cognition-pack expansion
(test_language_pack_cache): en-core-cog-085 → en-core-cog-091.
6. Holdout tests fail without CORE_HOLDOUT_KEY or local plaintext
(test_eval_holdout_split + test_transitive_surface): add
_requires_holdout skip-marker mirroring _decrypt_holdout's contract;
gate the transitive_surface holdout iteration on the same check.
7. Byte-identity surface guards regressed after the gloss-aware
composer landed (test_realizer_guard_holdout, test_prompt_diversity_runner,
test_register_substantive_consumption): re-pin to current surfaces
("Light is a visible medium that reveals truth." replaces "Light is a
source of revelation that makes things knowable.", etc.). The guard's
regression-catching role is preserved by pinning current output going
forward; the new gloss-driven phrasings are visibly more grounded.
Touched 14 test files: 176 passed, 4 skipped (holdout-gated), 0 failed
on a targeted re-run. No production code touched.
* feat(evals): add deterministic symbolic equivalence generated corpus
* feat(evals): add symbolic equivalence replay helpers
* feat(evals): load generated symbolic equivalence corpus
* feat(evals): emit symbolic equivalence replay manifest
* feat(symbolic): support multivariable integer polynomials
* feat(symbolic): support exact rational polynomial coefficients
* feat(symbolic): align equivalence API with multivariable normalization
* test(ADR-0131.1.B): reconcile v1 expectations to v1.B scope expansion
The v1.B refactor (univariate int → sparse multivariable Fraction) deliberately
admits multivariable polynomials and constant-denominator division. The v1
dataset and tests pinned the old refusal behavior, so the lane runner reported
wrong=4 and 10 unit tests failed.
Reconcile:
- cases.jsonl: flip sym-eq-v1-0029 ('x+y' vs 'x+1') and sym-eq-v1-0030
('x/2' vs 'x') from expected=refused to expected=not_equivalent; rename
categories to multivariable_distinct / constant_denominator_distinct;
extend provenance with adr-0131.1b:scope-expanded.
- generated_cases.py: split _refusal_cases into scope_expanded (admits)
and templates (still refused); the first two adversarial cases move to
the scope-expanded list with expected=not_equivalent.
- test_math_symbolic_normalizer.py: replace test_undefined_variable and
test_unknown_operator_division with positive scope-expansion tests +
symbolic-denominator refusal; rewrite TestPolynomialInvariants for the
new terms/variables constructor (Polynomial(terms={...}, variables=(...)))
with float-rejection and zero-coef-collapse invariants.
- test_math_symbolic_equivalence.py: TestRefused.test_empty_left reason
string matches new normalizer error; flip multivariable + constant-
denominator cases to NOT_EQUIVALENT; add symbolic-denominator-refused
case; relax canonical_a assertion in test_a_normalizes_b_refuses (engine
now zeroes both on either-side refusal).
- report.json + manifest.json: regenerated; lane PASS 185/185 wrong=0.
Lane invariants reaffirmed by the new tests: wrong==0, refusal-first for
truly out-of-scope inputs (symbolic denominator, transcendental, malformed,
negative exponent), determinism via byte-equal report.
ADR-0131 Benchmark 1 substrate — the primary discriminator for the
mathematics_logic expert promotion under the architecture-aligned
benchmark composite proposed in ADR-0131.
WHAT LANDED:
generate/math_symbolic_normalizer.py
Deterministic univariate polynomial normalizer. Scope: single
variable, integer coefficients, +/-/*/** operators, parens, no
division, no transcendentals. Pipeline: tokenize -> recursive-
descent parse -> expand-and-collect -> canonical string. Refusal
is first-class via SymbolicError; out-of-scope inputs refuse
rather than guess (preserves wrong == 0).
generate/math_symbolic_equivalence.py
check_equivalence(a, b) -> EquivalenceVerdict
Returns EQUIVALENT / NOT_EQUIVALENT / REFUSED with canonical
strings + reason. Compares byte-equal canonical forms.
evals/math_symbolic_equivalence/v1/
cases.jsonl — 30 hand-curated cases across 18 algebraic
identity categories + 2 out-of-scope refusals.
Coverage: commutative, distributive, square +
cube of binomial, difference of squares, FOIL,
collect like terms, zero cancellation, factoring,
exponent combination, unary negation.
runner.py — CLI entry point. Loads cases, builds report,
writes JSON, exits 0/1 on gate pass/fail.
README.md — methodology, scope, dataset categorization,
exit criterion, baseline result.
tests/
test_math_symbolic_normalizer.py — 44 tests covering parser,
algebra primitives,
canonical-form invariants,
and every refusal path.
test_math_symbolic_equivalence.py — 16 tests on the public
check_equivalence API.
test_adr_0131_1_symbolic_equivalence_lane.py
— 8 tests gating the lane:
dataset integrity, exit
criterion, wrong == 0,
determinism (byte-equal
report across runs).
EMPIRICAL RESULT (the lane PASSED):
correct = 30 / 30 (100.0%)
wrong = 0 / 30 (wrong == 0 invariant satisfied)
refused = 0 / 30 (refusals all matched expected)
correct_rate = 1.00
exit_criterion: PASSED (>= 0.95 required)
CONTRAST WITH ADR-0127-0128 GSM8K TRAIN-SAMPLE RESULT (0/0/50):
This is the first benchmark on the mathematics_logic lane where
the architecture's structural strengths fully express. The result
is the empirical inverse of the GSM8K result — and that's
exactly the architecture-benchmark fit ADR-0131 was written to
re-target toward.
REGRESSION: 1033/1033 existing tests green across math + ADR-0126
+ pack ratification + runner. Zero regressions.
SCOPE DISCIPLINE (per ADR-0131.1 v1 plan):
v1 deliberately narrow (univariate, integer, polynomial). Future
ADR-0131.1.B expansions documented in README: multi-variable,
rationals, larger dataset (~500), sealed holdout per ADR-0119.7
pattern.
PARALLEL WORK (per ADR-0131 plan to run all 3 sub-phases concurrently):
- ADR-0131.2: CORE-native teaching-corpus eval (separate PR)
- ADR-0131.3: bounded-grammar word-problem set (separate PR)
These are independent of ADR-0131.1; no shared files, no
cross-PR coordination required beyond final composite gate.
Docs-only coordination artifact for the ADR-0131 post-GSM8K pivot.
Adds an implementation plan that defines the composite proof corridor,
claim boundaries, phase sequencing, and non-negotiable acceptance gates.
Docs-only PR. Follow-up to ADR-0127-0128-RESULTS' Path-B trigger.
Replaces ADR-0120's GSM8K-coverage requirement for the
mathematics_logic expert promotion with a composite gate over
three architecture-aligned benchmarks:
Benchmark 1: Symbolic equivalence (~500 algebra cases, public
+ sealed split). Primary discriminator — CGA exact-recall.
Pass: correct_rate >= 0.95, wrong == 0.
Benchmark 2: CORE-native teaching-corpus eval. Internal
consistency lane sourced from ratified packs (en_arithmetic_v1
+ en_units_v1 + en_numerics_v1). Grammar matches by
construction (no paraphrase-variance gap).
Pass: correct_rate >= 0.95, trace_hash byte-equality, wrong == 0.
Benchmark 3: Bounded-grammar word-problem set (~150 cases,
pre-filtered to ADR-0126/0127/0128 parser scope). Demonstrates
end-to-end pipeline determinism on the in-scope distribution.
Includes adversarial out-of-grammar probes.
Pass: correct_rate >= 0.95, wrong == 0.
Three benchmarks (not one) prevent overfitting per ADR-0114a
and force the math expert to demonstrate three distinct
architectural properties (algebraic correctness, internal
consistency, end-to-end pipeline determinism).
GSM8K stays as a stress-test lane the math expert RUNS but is
NOT gated on. Refusal counts reported in expert-claims artifact
as honest disclosure.
Other 12 ADR-0120 expert-promotion checks UNCHANGED.
Status: Proposed. The contract revision (removing GSM8K from
the gate) is a follow-up implementation PR after sub-phases
0131.1-0131.6 land the new benchmark substrate.
Integrates en_units_v1 (#164) + en_numerics_v1 (#163) into the
ADR-0126 candidate-graph parser. Loader merge (re-exports from
numerics_loader.py give single import path), pack-aware unit
canonicalization (handles irregular plurals like feet/children
via lookup_unit), indefinite-quantifier refusal (ADR-0128.4 —
'some'/'many' emit no candidates, preserving wrong==0), and
widened initial-possession shapes:
- <Entity> has N <unit> [of <substance>] (ADR-0127 substance qualifier)
- There are N <unit> [in <place>] (implicit-subject shape)
Plus: pack-backed cardinal grounding in math_roundtrip._value_grounds
(widens word-number coverage from hard-coded 0-12 to full numerics
pack cardinal table + compound rule). Op-pattern trailing prep
alternation gains of/for/with for substance qualifiers.
REGRESSION: 1050/1050 tests green across math + ADR-0126 + ADR-0127
ratification + ADR-0128 ratification + runner.
EMPIRICAL RESULT (the Path-B trigger ADR-0126/0127/0128 named):
correct = 0/50 wrong = 0/50 refused = 50/50
on evals/gsm8k_math/train_sample/v1/cases.jsonl
Per ADR-0127's exit criterion (correct >= 10/50, wrong == 0):
**MISSED** — the full deterministic design (candidate-graph
topology + units pack + numerics pack + pack-aware parser) does
not move the GSM8K-math lane. This is the real Path-B trigger.
WHAT WORKS (synthetic verification, 6/6 cases solve end-to-end):
- 'Jan has 5 apples. Jan buys 3 apples. ...' -> 8
- 'Sam has 10 feet of rope. Sam uses 3 feet of rope. ...' -> 7
- 'There are 5 kids in camp. ...' -> 5
- 'Sam has 10 children. Sam loses 2 children. ...' -> 8
- (money + time-dimension variants pass)
WHY GSM8K STAYS AT ZERO: real GSM8K problems carry compound
linguistic structure (pronouns across statements, possessives,
subordinate clauses, multi-word entities, multi-step inference)
that no amount of pack vocabulary addresses. Per-sentence parse
rate improved measurably on simple shapes; joint problem-level
pass rate stayed at zero because every real problem contains at
least one sentence the parser still cannot handle.
Full results + Path-B recommendation in
docs/decisions/ADR-0127-0128-RESULTS.md. The substrate
(architecture + packs) stays load-bearing in main; the math
expert promotion path retargets to a benchmark where exact
recall and determinism are the discriminators (proposed
ADR-0131).
Exhaustive English linguistic-form ontology for quantities:
cardinals (0..20 + tens + magnitudes + compound rule), ordinals
(1st..31st + decade/magnitude forms), named fractions (1/2..1/10
+ sixteenth/thirty-second) + symbol forms (½ ¼ ¾ ⅓ ⅔ ⅛ ⅜ ⅝ ⅞),
multipliers (double/triple/twice/half), quantifiers with
semantic_type (indefinite triggers refusal at parse time —
preserves wrong==0), comparison anchors migrated for
ratifiability, number-format regexes with positive/negative
corpora.
Loader API in language_packs/numerics_loader.py (sibling module
to be merged into main loader after Gemini's ADR-0127 loader
lands, to avoid concurrent merge conflict).
Ratification invariants gated: cardinal/ordinal/fraction
exhaustiveness, quantifier semantic-type closed set, format-regex
test corpora (10+ positive/negative per format, ambiguity
refused), manifest checksums = SHA-256 of bytes-on-disk,
self-sealing mastery report.
Cross-references en_units_v1 (Gemini ADR-0127): fraction symbols
authoritative here; en_units_v1 symbol-affix table will point to
these entries.
No parser changes (deferred to 0128.3-0128.6). No train-sample
re-run (joint exit gate with ADR-0127 runs after both packs land).
Total: 130 lexicon entries across 7 kinds.
Lanes: smoke 67/0/0, packs 6/0/0, ADR-0128 suite 243/0/0.
Operator-supplied review of 'Beyond Traditional Pedagogy' triggered
a literature confirmation pass and a structural cross-walk against
CORE's teaching loop. Three artifacts:
1. ADR-0129 (DEFERRED) — Spaced reviewed-correction replay.
Maps onto retrieval-with-spacing literature (most robust finding
in cognitive psychology). Deterministic re-run of past
corrections at fixed cadence to verify they still produce
intended outcomes; failures emit operator-visible events
(no auto-correction). Deferred pending GSM8K-math Path-A/B
resolution + observed incident triggering un-deferral criteria.
2. ADR-0130 (DEFERRED) — Pre-articulation calibration logging.
Maps onto metacognitive prediction-outcome literature. Logs
CORE's pre-correction prediction; emits gap event on
correction acceptance. Provides empirical signal for 'is CORE
actually getting better' across pack-version cohorts. Deferred
pending same conditions as ADR-0129; the two compose if
un-deferred.
3. SESSION-2026-05-23 session note. Documents the review process:
literature confirmation pass (productive failure overstated,
retrieval transfer weaker than claimed, embodied cognition
replication crisis), missed frameworks (worked-example effect,
expertise reversal, CLT, deliberate practice, Bloom's 2-sigma),
structural cross-walk to CORE architecture (12 mappings), and
the rationale for ADRs 0129 + 0130 over alternative ports
(productive failure rejected as inverse of wrong==0; pre-testing
same; embodied learning N/A).
No code changes. Docs-only PR; lands independently of in-flight
ADR-0126 / 0127 / 0128 substrate chain.
Diagnostic from ADR-0126's first train-sample run (0/0/50): every
refusal happens at the first statement of each problem, and every
refused first statement fails on the unit-of-measurement construction,
not on the operation grammar. Adding more verb regexes is the per-axis
treadmill that produced 4 zero-lift ADRs. Units form a finite, externally
well-defined ontology (NIST SI tables, currency, English container nouns)
that is semantic substrate the candidate-graph parser was designed to
consume.
Scope:
- en_units_v1 pack: dimensions, units (<=60), containers, rate connectors
- conversions.jsonl: directed weighted graph of within-dimension unit pairs
- 3 new initial-possession shapes + rate-declaration extractor in the
candidate parser
- Round-trip filter gains optional pack-typed-unit check
- Solver gains dimensional canonicalization helper (shortest path through
conversion graph); fired edges join SolutionTrace.steps for replay
- Pack ratification invariants: round-trip identity, per-dimension
connectivity, path consistency, canonical unit per dimension
Wire the same train-sample exit criterion as ADR-0126 (correct >=10/50,
wrong==0). If passed -> sealed holdout. If still missed -> Path B
trigger is REAL (full deterministic design with units substrate failed),
demote GSM8K, re-target math expert promotion.
Also commits the empirical evidence: train_sample/v1/runner.py swapped
_score_one -> _score_one_candidate_graph; report.json baseline 0/0/50
confirming the candidate-graph topology refuses cleanly without units
substrate.
P3 — generate/math_candidate_graph.py:
Branch enumeration over per-sentence candidate choices (Cartesian
product, cap=64). Per-sentence ambiguity tiebreaker via most-grounded-
slots-wins (transfer beats subtract when 'to Tom' grounds). Decision
rule: 0 admissible -> refuse; 1 -> emit; >=2 same answer -> emit;
>=2 different answers -> refuse (preserves wrong==0 on genuine
ambiguity). End-to-end parse_and_solve(text) -> CandidateGraphResult.
Question extractor added to math_candidate_parser.py (CandidateUnknown,
total + entity question shapes mirroring math_parser).
22 new tests. Permissive verbs ('bought', 'ate', 'bakes') now produce
correct answers via the candidate-graph path; ambiguous 'gives to Tom'
resolves to transfer reading (Tom gets the apples) deterministically.
P4 — evals/gsm8k_math/runner.py:
New sibling function _score_one_candidate_graph(case) -> CaseOutcome.
Identical shape to _score_one; swaps parse_problem for parse_and_solve;
preserves verifier/realizer/expected-answer stages. Callers (e.g.
PR #160's train_sample/v1/runner.py) substitute the new function in
one line to evaluate the candidate-graph topology.
9 new wiring tests. Three groups:
- No regression: cases legacy solves, new also solves.
- Lift: cases legacy refuses, new solves (the architectural payoff).
- Wrong==0: out-of-grammar refuses, never wrong.
Regression: 714/714 existing math + runner tests still green.
ADR-0126 total: 74/74 tests green across P1+P2+P3+P4.
Sibling to math_parser.py — pure candidate-extraction functions that
emit list[CandidateOperation] per sentence without mutating any state.
State threading defers to P3 (per-branch graph assembly).
Topology change vs legacy:
- No first-match-wins; every verb-kind regex runs independently.
- Ambiguous verbs ('gives', 'returns') emit multiple candidates;
P1's round-trip filter + P3's decision rule resolve.
- Out-of-grammar sentences return [], NOT ParseError. Empty list
is the deterministic 'no candidate' signal.
Permissive verb tables (imported from math_roundtrip.KIND_TO_VERBS)
mean past-tense and production verbs ('bought', 'ate', 'bakes')
that the legacy parser refused are now admissible — the round-trip
filter is the safety mechanism, not regex narrowness.
P2 scope (canonical Subject-verb-Value-Unit-[to-Target] shape only):
- extract_initial_candidates(sentence) for 'X has N units'
- extract_operation_candidates(sentence) for add/subtract/transfer
Out of scope (deferred to later sub-phases):
- Pronoun resolution / unit inheritance (needs per-branch state)
- Multiply / divide / rate / comparison (same machinery, more matchers)
Regression: existing math suite 701/701 green. Zero changes to
math_parser.py, math_solver.py, math_verifier.py, math_realizer.py.
The wrong-answer firewall for the candidate-graph parser topology.
A CandidateOperation carries an Operation plus source-span provenance
for every content slot the parser claimed (verb, value, unit, actor,
transfer target, comparison reference). roundtrip_admissible() checks
each slot grounds in the source span AND the matched verb is
registered for the claimed kind.
Two consequences:
- A regex that mis-reads 'loses' as add fails (loses not in ADD_VERBS).
- A regex that hallucinates a number/unit not in source fails to ground.
KIND_TO_VERBS is the new single source of truth for {kind -> verbs};
P2 will refactor math_parser to consume it. Verb tables are
permissive by design (much wider than current narrow regex tables)
because the filter rejects wrong candidates downstream — narrowness
is no longer the safety mechanism.
Deterministic: pure byte/regex containment. No randomness, no
learning, no approximation. Preserves wrong==0, trace_hash byte-
equality, replay determinism.
Architectural pivot from per-axis grammar expansion (ADR-0122/0123/0123a/
0123b, all 0/1319 sealed lift) to candidate-graph topology with round-trip
admissibility filter. Converts compound-gap failure from multiplicative
p^k to parallel 1-(1-p)^k.
Adds new invariant: round-trip admissibility (op slots must reconstruct
to byte-equal source sentence under whitespace/case normalization).
Preserves wrong==0, trace_hash byte-equality, pack-binding, replay
determinism, no stochastic sampling.
Exit criterion: 50-case GSM8K train-split sample (unsealed) must show
correct >=10/50 with wrong==0 before any sealed-holdout run. If miss,
escalate to Path B (benchmark re-selection).
Supersedes ADR-0123b (never opened as PR).
Wraps existing math pipeline (parser -> solver -> verifier) against
PR #159's 50-case train sample. Emits deterministic report.json with
per-case verdicts. CLI exit code reflects exit criterion
(correct >= 10 AND wrong == 0).
Baseline against current parser: 0 correct / 0 wrong / 50 refused.
This baseline is the inner-loop gradient signal for ADR-0126's
candidate-graph parser (in flight on feat/adr-0126-candidate-graph).
Registers tests/test_adr_0126_train_sample_runner.py under
'core test --suite math' so the wrong == 0 invariant becomes a hard
CI gate per ADR-0114a Obligation #4 (refuse rather than confabulate).
Depends on PR #159 (gemini/adr-0126-train-sample). Rebase onto main
after #159 lands.
Closes 5 of 8 surface-form gaps Gemini identified in Task 5 on the
99 comparison-bearing sentences my ADR-0123 substrate currently refuses
in the sealed holdout. Pure regex / parser-state work — no graph,
solver, verifier, or pack changes; preserves wrong==0 discipline.
Expansions (in safety order)
- Group 8 (verb): comparison verbs widened from {has} to {has, have,
had, gets, get, got, takes, take, took, buys, buy, bought}.
"lost"/"won" excluded — they semantically invert direction.
- Group 3 (word-form numbers): _WORD_NUMBERS {one..twelve} accepted
wherever digit values are. _parse_compare_number helper centralizes
the dispatch.
- Group 4 (ellipsis / implicit unit): unit slot made optional in
multiplicative patterns (solver already infers unit from reference
state); added "twice|N times as much", "twice|N times the
number/amount of <unit>" variants.
- Group 1 (subjects / references): actor/reference slots widened from
bare proper noun to {proper noun, "the <noun>" collective,
pronoun}. Pronouns resolve via state.last_singular_subject; missing
prior subject raises ParseError (no silent emission with empty
actor). New _resolve_compare_entity helper canonicalizes "The boys"
/ "the boys" to the same entity string.
- Initial-possession + question patterns widened symmetrically so
"the X" subjects round-trip end-to-end:
- _INITIAL_HAS_RE accepts "the <noun>" subject + has/have +
digit-or-word value
- _Q_ENTITY_RE accepts "the <noun>" entity + do/does auxiliary
- _Q_TOTAL_RE now tried first (specificity-ordered) so "do they
have" doesn't get greedily matched as entity="they"
Deferred (per Gemini Task 5c recommendation)
- Group 2 (age): needs new "years_old" attribute model
- Group 5 (nested): needs compound y = mx + c solver operation
- Group 7 (currency): low volume (2 cases), defer
- Group 6 (compound multi-clause "and" split): scoped out of this
PR to keep the wrong==0 risk profile tight; safer to land after
Gemini Task 6 confirms current expansion doesn't introduce
misparses on the sealed set
Test coverage
- 507 existing math + ADR-0122 + ADR-0123 tests pass (no regressions)
- 16 ad-hoc smoke cases pass (3 baseline + 3 Group 8 + 3 Group 3 +
3 Group 4 + 3 Group 1 + 2 refusal guards + 1 rate cross-check)
- smoke suite 67/67, algebra suite 82/82 green
Expected sealed lift
- Gemini Task 5 catalog projected ~65/90 strict-comparison-only
cases unblocked by the 5 included groups (71/99 comparison-bearing
sentences). Empirical sealed measurement pending Gemini Task 6;
PR will be updated with the actual correct/wrong/refused bucket
counts once measured.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
ADR-0123-parser-comparison-phrasing as the **surface increment** on
PR #155's substrate (commit c9bd5d4). Closes the last architectural
gap in the comparison-phrasing class: before this commit, the
substrate's solver evaluated comparison problems successfully but
realize() crashed with `unknown operation_kind 'compare_additive'`
when asked for show-your-work prose.
Substrate (PR #155) already shipped:
- `Comparison` typed graph operand
- `compare_additive` / `compare_multiplicative` operation kinds
- parser patterns for the four canonical surfaces
(N more / N fewer / twice / N times / half)
- solver + verifier wiring + pack lemmas
(en-arith-006 compare_additive, en-arith-007 compare_multiplicative)
This surface adds:
- `_compare_additive_sentence(step)` rendering `direction='more'|'fewer'`
- `_compare_multiplicative_sentence(step, entity_units)` rendering
`direction='times'|'fraction'`
- two new branches in `_step_sentence` dispatch
- `_step_sentence` signature widened with optional `entity_units` map
(derived once-per-trace in `realize()` from `graph_initial_state`)
- ADR-0123-parser-comparison-phrasing.md (~15 invariants, substrate
+ surface decomposition rationale, multi-construction barrier
inheritance)
- 26 invariants pinned across canonical surfaces, plurality
independence, byte-determinism, refusal discipline, and
backwards-compatibility with the pre-comparison realizer templates
End-to-end pipeline now operates on all four canonical comparison
shapes:
parse_problem(
"Alice has 5 apples. Bob has 3 more apples than Alice. "
"How many apples does Bob have?"
) -> solve() -> realize().as_prose() ->
"Alice has 5 apples. Bob has 3 more apples than Alice, giving Bob
a total of 8 apples. Bob has 8 apples."
Measurement (this PR):
- 26/28 direct ADR-0123 tests pass; 2 skipped (CORE_HOLDOUT_KEY)
- `core eval cognition` byte-identical: 100/100/100/100
- ADR-0118 stepped-realizer templates re-render byte-identically
- Substrate measurements continue to hold
Honest non-result: sealed `correct_rate` stays at 0/1319. The
realizer cannot create matches the parser refuses; the multi-
construction barrier the substrate ADR documented holds at the
surface layer too. Cumulative lift signal expected only after the
3rd/4th foundational class lands (per ADR-0121's revised
sequencing). `wrong == 0` holds by construction — realizer only
renders successful traces.
Pre-existing failure noted (not introduced by this PR):
`tests/test_adr_0085_gloss_aware_cause.py::test_flag_off_metrics_byte_identical`
fails on substrate base (c9bd5d4) without these changes — an
ADR-0085 cognition baseline drift unrelated to the realizer.
