- 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.
Implements the PropositionGraph epistemic carrier (ADR-0144):
recognition/carrier.py — EpistemicTransition, EpistemicNode, EpistemicGraph.
Frozen, JSON-serializable, byte-deterministic. EpistemicNode wraps a
RecognitionOutcome with an append-only provenance chain; epistemic_state
property tracks last transition's to_state or outcome.state when empty.
recognition/connector.py — epistemic_node_to_graph_node(). Maps an admitted
EpistemicNode's FeatureBundle (agent/relation/count/unit) to a GraphNode
for the generation-side articulation planner.
CognitiveTurnPipeline gains a recognizer: DerivedRecognizer | None param
(default None — all existing callers unaffected). When attached, run()
calls recognize() at the top of every turn and wraps admitted outcomes in
an EpistemicGraph. CognitiveTurnResult.epistemic_graph carries it.
RuntimeConfig.recognition_grounded_graph: bool = False — opt-in flag that
replaces the intent-derived PropositionGraph with one derived from the
admitted EpistemicNode via the connector.
RatificationOutcome gains three specific PASSTHROUGH sub-values
(PASSTHROUGH_NO_FIELD / NO_VOCAB / NO_VERSOR) for _ratify_intent
observability (ADR-0142 debt 1). All normalise to "passthrough" before
trace_hash so pre-ADR-0144 hashes are byte-identical.
24/24 acceptance tests pass; 67/67 smoke tests pass; no regressions.
