The ratified, flag-ON v1b categorical band served "all dog are mammal" for
every noun: the A/E/I/O templates supply all/no/some + are, which demand a
plural, and the slots were filled with singular canonical entity ids. Four
of the 47 ratified corpus cases were affected, and wrong=0 never noticed
because every verdict was correct — only the prose was wrong.
Two fixes that compose into a closed round trip:
1. generate/morphology.py becomes the single owner of the number RULES
(Phase 2A gave the TABLES one owner). Both directions live there:
pluralize + singularize, over lexicon.IRREGULAR_PLURALS /
IRREGULAR_SINGULARS, with mass-noun and compound-head handling.
templates.pluralize and reader._singularize were two independent copies
of the regular suffix rules that disagreed about which irregulars they
knew; both now delegate.
2. render._display_noun re-inflects at render time and swaps _ for a space,
so compound ids read "guard dogs" rather than "guards dog" or
"guard_dog".
Result: reader gives wolves -> wolf, renderer gives wolf -> wolves. The
round trip closes.
0 malformed of 47 (from 4)
reader-vs-reader singularization 20/20 (from 8/20), 0 silently wrong
s_surface_match_rate 0.0 -> 0.625, now EQUAL to s_renderable_rate, so the
only remaining losses are surfaces the renderer cannot express at all
NEAR-MISS — widening a reader broke soundness, caught by the lane:
Routing the reader through the full 29-entry table first produced wrong=1 on
band v6-EX. ds-ex-0012 ("No fish are mammals. Therefore some fish are
mammals.") answered invalid where gold is refuted.
_singularize returning None makes the reader REFUSE, and the serving
composer tries the categorical band FIRST, falling through to more capable
bands. "fish" previously returned None (it matches no suffix rule), so v6-EX
got the case and decided it correctly. Resolving "fish" made v1b accept a
sentence it cannot decide.
Fixed by a principle, not a patch: a number-INVARIANT form is ambiguous in
number — "fish are mammals" is plural, "a fish is a mammal" is singular, and
the token cannot tell you which — so a reader that must not guess number
declines it. lexicon.INVARIANT_NUMBER is derived from the singularizer's own
key == value rows, so the rule cannot drift from the table.
=> Coverage and correctness are different axes. Fixing a corrupted VALUE is
safe; widening ACCEPTANCE changes which band answers, and in a
first-match composer that turns a right answer into a wrong one. Same
family as ADR-0261 5.1 refuse-don't-drop.
Also fixed, found by testing the inverse law: the two number tables were not
mutual inverses. The pluralizer lacked cactus->cacti, fungus->fungi,
die->dice and the invariants aircraft/means/offspring, so CORE could read
"cacti" but wrote "cactuses", and would have written "aircrafts", "meanses",
"offsprings". No round trip can close across a non-invertible table.
THE LANE SHA PINS ARE BLIND TO SERVED ENGLISH:
2B changed 4 served surfaces and the pins came back 11/11 byte-identical.
The deduction_serve_v1 hashed report holds only n/counts/by_gold/
correct_by_gold/all_cases_correct/mismatch_examples — no prose at all.
Confirmed by sabotage: with _display_noun returning "SABOTAGE_" + ..., so
every clause reads "all SABOTAGE_dogs are SABOTAGE_animals",
11 lane SHA pins -> 11/11 byte-identical, blind
test_deduction_serve_lane + _license -> 20 passed, blind
Phase 1 grammar_roundtrip -> 3 tests RED, caught it
This corrects #129: byte-identity of the pins is the arbiter for values and
verdicts, NOT for surface text, so the 2A/2B split is not a partition of
"changes users can see." Phase 2A's 11/11 conclusion still stands on its own
independent evidence (24/24 table-equality checks vs the pre-migration
literals), but the justification was thinner than stated.
Before Phase 1 no test in the tree would have noticed CORE's served prose
turning into word salad. That is exactly how "all dog are mammal" survived
on a ratified flag-ON band with wrong=0 intact.
Deliberately not fixed: mass-noun verb agreement ("all evidence ARE truth"
should be "is"). The copula is fixed text inside the templates, so agreeing
it changes the template shape rather than a slot, and no mass noun reaches a
categorical clause in any serve corpus. Recorded in render.py.
No lane pin edited — none moved.
[Verification]: in-worktree on CPython 3.12.13, uv sync --locked —
smoke 621 unchanged; deductive 403 passed (383 + 20 new/rewritten);
scripts/verify_lane_shas.py 11/11 (see blindness note above — gate on
grammar_roundtrip for surface work, not on these pins).
Collapses the duplicated closed English tables into generate/lexicon.py.
Measured on main @ 0948f7cd: the same facts were encoded up to five times
across the reading and writing paths, each copy written independently as a
successive deduction band landed.
The 2A/2B split is decided empirically per #129 — make the change, run the
11 pinned lanes, let byte-identity rule. Result: 11/11 byte-identical, so
this entire unit is 2A and nothing spilled into the authorization-gated 2B.
Collapsed to one object:
- connectives 3 identical copies (member, verb, cond_member)
- predicate display 2 identical 26-entry copies (semantic_templates,
templates)
- be-form inventory 5 copies, not the 2 §1.3 counted. The structural
test found realizer_guard._BE_AUX and
chat/runtime._BE_FORMS, which a COPULA-shaped grep
could never see.
Derived rather than duplicated, so they can no longer drift:
- STRUCTURAL = CONNECTIVES | {therefore}
- QUANTIFIER_TOKENS = QUANTIFIER_LEAD | QUANTIFIER_NON_LEAD
- NEGATION_BEARING_WITH_NOT = NEGATION_BEARING | {not}
- READER_IRREGULAR_SINGULARS = IRREGULAR_SINGULARS restricted to 8 keys
§1.3 re-measured while doing this, and it overstated the disease (plan
§1.9). Almost nothing contradicts:
- the "3 divergent plural tables" are 1 pluralizer + 2 singularizers,
i.e. inverse directions; comparing them as copies is a category error
- reader's 8 singulars are a STRICT SUBSET of member's 29 with the
difference in reader's favour empty, so its values are all correct and
only its coverage is short
- the "3 divergent quantifier sets" are 3 distinct facts; every/each lead
a clause but take singular nouns, so their absence from
PLURAL_QUANTIFIERS is correct
- english's negation set is a subset of member's, and the difference is
principled: v2-EN normalizes "<copula> not", v3-MEM refuses it
Exactly one genuine contradiction exists in the whole inventory:
discourse_planner maps is_defined_as -> "is" where the others map it to
"is defined as". Preserved as a register choice, pinned by test.
Found while reading, pinned as current behaviour for 2B to flip:
reader._singularize does NOT refuse uncovered plurals despite a comment
claiming it does — it falls through to a bare -s strip, so news -> new and
species -> specy, exactly the corruptions member.py's table comment says
its table exists to prevent.
Two 2A exit criteria were unmeasurable as written and are replaced:
- "Jaccard -> 1.00" cannot work. measure_grammar_seam.py scans source
literals, so unifying a fact removes it from those files and Jaccard
FELL, 0.083 -> 0.023 — the success direction reported by a metric
shaped to read like failure. Replaced with an object-identity count:
3 distinct objects behind 8 names, from 8-behind-8. Value comparison
cannot tell a shared object from two equal copies.
- "one table per fact" presumed §1.3's inventory was right. The report now
separates must-be-one-object (all UNIFIED) from related-but-distinct
(6 relations, all HOLD).
ADR-0258 §5 already decided morphology's destination is a ratified pack,
triggered by a grc/he member band. No such band exists, so the promotion is
correctly deferred and lexicon.py is a staging area, not a rival home — no
new ADR. Destination measured for whoever picks it up: packs/en/morphology
.jsonl has 9 records and zero irregular plurals, features.number has no
consumer, and _pack_morph_roots_for reads a top-level "root" key that 0 of
31 records across all four packs define, so it returns {} every call.
[Verification]: in-worktree on CPython 3.12.13, uv sync --locked —
smoke 621 unchanged; deductive 383 (364 + 19 new);
scripts/verify_lane_shas.py 11/11 byte-identical.
Adds comprehension_propositional — the comprehension organ now reads the classic
propositional ARGUMENT FORMS end-to-end into the flagship deductive_logic ROBDD
oracle (the most robustly independent gold in the repo). The neutral MeaningGraph
now feeds FOUR independent oracles (set-membership, syllogism-validity,
total-ordering, propositional-entailment) from one interlingua — the Option-B
interlingua thesis validated.
reader.py: propositional templates (atoms are chunked NP ids; fits the existing
entities + n-ary relations + negation model — NO interlingua change, propositional
is not arithmetic-quantities):
- "if <P> then <Q>" -> implies(P, Q)
- "not <P>" -> asserted(P, negated=True)
- "<P> or <Q>" -> or(P, Q)
- "<P>" (single token) -> asserted(P) (bare-atom, single-token only to
keep the parse-or-refuse floor)
- "therefore <prop>" -> query of the same predicate
Relations now carry a negated flag end-to-end (asserted negation).
projectors.py: to_deductive_logic serializes propositional relations/query into
formula strings (keyword operators the oracle tokenizer accepts); returns None
(refusal) unless the comprehension is purely propositional, so categorical/ordering
comprehensions never leak into the entailment oracle.
evals: new evals/propositional_logic/v1 (12 cases — modus ponens/tollens,
hypothetical & disjunctive syllogism, the affirming-consequent / denying-antecedent
fallacies which the oracle marks "unknown"; gold = oracle verdict) + gold-only
runner + evals/comprehension/propositional_runner.py. Oracle "refused" (formula
unevaluable) is treated as a decline, never a wrong.
Scores: comprehension_propositional 12/12 wrong=0 (full coverage); no regression on
the 3 existing lanes (8/8, 7/8, 7/8). Capability index breadth 6->7, score
0.917231 -> 0.928622, wrong_total 0, digest 51df7bba…
Tests: reader propositional templates; to_deductive_logic projector tests;
end-to-end full-coverage wrong=0; propositional generative round-trip added to the
wrong=0 property suite (verified to BITE under a reversed-implies mutation);
capability breadth 6->7. 115 targeted + 87 smoke green. Lane SHAs 8/9 (sole miss =
public_demo env wall-clock flake; deductive_logic_v1 unchanged).
Recovers the multi-word-NP cases the reader previously refused, by adopting ONE
principled canonicalization contract (evals/comprehension/CANONICALIZATION.md) that
the reader AND the gold lanes both follow — so a committed answer can only match
gold or refuse, never silently mean something else.
Contract: a noun-phrase slot -> tokens lowercased, joined with "_"; a plural class
slot singularizes its head first ("metal objects"->"metal_object",
"North station"->"north_station", "Level one"->"level_one"). JOIN is chosen over
head-word-only ("metal objects"->"metal") because head-word-only is
information-destroying — it collapses "metal objects" and "metal tools" into one
false identity, itself a wrong=0 hazard.
reader.py: slot-based templates chunk multi-token NPs (_chunk / _chunk_class
replace the single-token _one / _one_class). Reserved-function-word guard fires only
INSIDE a multi-token slot (a lone "A" item is content, not the article). Still
parse-or-refuse: reserved-word leaks ("Compare beta with beta in the same order"),
non-pluralizable class heads (adjectival "trained"), and the ambiguous adjacent
two-NP subset query ("Are all <Xs> <Ys>?") all REFUSE.
gold (the contract update, logic-preserving — only term NAMES change):
- sy-v1-0008: metal/soft -> metal_object/soft_object (was head-word-only)
- to-v1-0005: red -> red_rank (was head-word-only)
- to-v1-0004: prose made internally consistent ("is after", "north station") +
north -> north_station (original prose used "North station" in the fact but
"north" in the query — a latent inconsistency)
- to-v1-0007: already conformed (level_one…), no change
Gold-only integrity runners stay 8/8 both lanes (structure+query+gold consistent).
Scores: set_membership 8/8, syllogism 6/8->7/8, total_ordering 4/8->7/8, all
wrong=0. Capability index re-frozen: score 0.814356 -> 0.917231, breadth 6,
wrong_total 0, digest 13d7db6c…
Tests: reader chunking + refusal tests; multi-word generative round-trip added to
the wrong=0 property suite (verified to BITE under a head-word-only mutation —
collapsed ids produce a wrong verdict the test catches); pinned counts updated.
100 comprehension/capability targeted + 87 smoke green.
Phase 2a r2/r3/r4 of the redefined plan: the general comprehension reader now
reads THREE independent-gold reasoning domains end-to-end (prose -> MeaningGraph
-> projection -> independent oracle -> answer vs gold), all wrong=0, and all
three are wired into the capability index.
reader.py — new domain-agnostic templates (function words + order; parse-or-refuse):
- categorical E/I/O: "no Xs are Ys"->disjoint, "some Xs are Ys"->intersects,
"some Xs are not Ys"->some_not (A "all Xs are Ys"->subset already existed)
- "therefore <categorical>" -> conclusion QUERY (same neutral predicate vocab)
- comparative facts: "<X> [is] <comp> [than] <Y>" -> less(...), closed
less/greater comparator lexicon, elided-copula support
- sort query ("sort ascending|descending", "... order from <low> to <high>")
and compare query ("compare <X> with <Y>")
- clause-splitting on commas / leading and|or for multi-clause sentences
projectors.py — to_syllogism (premises + validity conclusion, finite-model size 3)
and to_total_ordering (less-facts + sort/compare). Both return None when nothing
is honestly askable of their oracle (caller treats as refusal).
capability_index — wire 3 comprehension lanes into ADAPTERS; re-freeze baseline
breadth 3->6, capability_score 0.919641->0.814356 (geomean falls BY DESIGN as
honest partial-coverage domains join; wrong_total stays 0). digest 0a98b9b4...
Scores: set_membership 8/8, syllogism 6/8, total_ordering 4/8 — all wrong=0.
Multi-word NP handling is DEFERRED on purpose, not missed: the gold lanes
canonicalize multi-word NPs three contradictory ways ("North station"->"north",
"Level one"->"level_one", "metal objects"->"metal"), so no single general rule is
wrong=0-safe. The reader refuses multi-word NPs until the gold lanes carry a
canonicalization contract. Every refusal is a genuine harder phenomenon
(multi-word NP, adjectival predicate, trailing tokens) — never a readable case
silently dropped.
Tests: reader templates, projector unit tests, syllogism/total_ordering
end-to-end wrong=0 with pinned counts, capability breadth 3->6. 138 targeted +
87 smoke green. Lane SHAs 8/9 (sole miss = public_demo env wall-clock flake).
Disciplined Path β (field decode α was empirically falsified). Reads S-P-O
structure SYMBOLICALLY from the token sequence via domain-agnostic templates
keyed on FUNCTION WORDS + ORDER, mints content as MeaningGraph entities/relations,
parse-or-refuse (wrong=0 at the comprehension layer).
Templates (set_membership): 'X is a Y' -> member; 'all Xs are Ys' -> subset;
'is X a Y?' / 'are all Xs Ys?' -> queries; definite-NP ('the X is a Y');
conservative singularization incl. irregulars (people->person), refusing
unknown morphology rather than guessing.
End-to-end: prose -> comprehend -> project -> INDEPENDENT set_membership oracle
-> answer vs gold. Result on the real v1 lane: 8 correct / 0 wrong / 0 refused
(full coverage, wrong=0). Cross-content generality (animals/professions/geography)
asserted. 14 reader unit tests + 3 end-to-end tests, each bites under its
violation. Additive only; invariants + capability index green.
Shay