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.
- Add LexicalResolution dataclass + resolve_entry() in chat/pack_resolver.py
that returns language, root, morphology_id, gloss, semantic_domains from
he/grc/en packs (lru-cached, first-match, full depth support).
- Extend GraphNode (generate/graph_planner.py) with optional language/root/
morphology_id fields (defaults preserve all call sites). Update as_dict()
to include them conditionally. ground_graph() now propagates depth.
- Generalize enrichment in core/cognition/pipeline.py:
- Per-subject resolution map using depth packs.
- Enrich all matching nodes before ground (subject→node map).
- Pass depth alongside recalled_words to ground_graph().
- Consume depth on articulation side:
- realize_semantic() and render_semantic() now accept/use language+root
for etymological/Logos framing on Hebrew/Greek nodes (e.g. "אמת (Hebrew
root: א-מ-ן) is defined as..."). English unchanged.
- Enrich oov_geometric_context with node_depths for future geometric
anti-unification using roots.
- Extend recognition/connector.py to forward depth from EpistemicNode
paths into GraphNode.
- Add full Hebrew turn test under realizer_grounded_authority flag.
- Update related tests (semantic realizer, OOV context, surface resolution).
- Cleaned legacy type() hack immediately on discovery (hard-stop rule).
All targeted tests green (52+ in slices), broad relevant suite 581 passed.
Invariants preserved: versor only at owned boundaries, exact recall,
immutable updates, no new legacy parsers. 3 pillars upheld.
Work continues tomorrow from this checkpoint.
