c1e723f185
- 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.
106 lines
3.6 KiB
Python
106 lines
3.6 KiB
Python
"""Intent-aware semantic templates for the realizer.
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Maps (IntentTag, relation_predicate) pairs to deterministic surface
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templates that use the seed pack's relation predicates (defines, means,
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grounds, supports, contrasts_with, corrects).
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Design constraints:
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- No LLM fallback
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- No random template selection
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- Deterministic: same (intent, predicate, subject, object) -> same surface
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- Uses seed pack vocabulary directly
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"""
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from __future__ import annotations
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from generate.intent import IntentTag
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_INTENT_TEMPLATES: dict[IntentTag, str] = {
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IntentTag.DEFINITION: "{subject} is defined as {obj}",
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IntentTag.CAUSE: "{subject} is grounded in {obj}",
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IntentTag.PROCEDURE: "first, {obj}; then, {subject} follows",
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IntentTag.COMPARISON: "{subject} and {secondary} are distinguished: {subject} {predicate_h} {secondary}",
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IntentTag.CORRECTION: "correction: {subject} {predicate_h} {obj}",
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IntentTag.RECALL: "recalling {subject}: {obj}",
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IntentTag.VERIFICATION: "{subject} is verified: {obj}",
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IntentTag.UNKNOWN: "{subject} {predicate_h} {obj}",
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}
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_PREDICATE_HUMANIZE: dict[str, str] = {
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"is_defined_as": "is defined as",
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"is_caused_by": "is caused by",
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"has_steps": "has the following steps",
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"contrasts_with": "contrasts with",
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"corrects": "corrects",
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"recalls": "recalls",
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"is_verified_as": "is verified as",
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"addresses": "addresses",
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"defines": "defines",
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"means": "means",
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"grounds": "grounds",
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"supports": "supports",
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"causes": "causes",
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"reveals": "reveals",
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"precedes": "precedes",
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"follows": "follows",
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"belongs_to": "belongs to",
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"answers": "answers",
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"is_grounded_in": "is grounded in",
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"is_distinguished_from": "is distinguished from",
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"implies": "implies",
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"entails": "entails",
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"requires": "requires",
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"verifies": "verifies",
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"evidences": "evidences",
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"orders": "orders",
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}
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def humanize_predicate(predicate: str) -> str:
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return _PREDICATE_HUMANIZE.get(predicate, predicate.replace("_", " "))
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def render_semantic(
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intent: IntentTag,
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subject: str,
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predicate: str,
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obj: str,
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secondary: str | None = None,
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language: str | None = None,
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root: str | None = None,
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) -> str:
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"""Render a semantic surface from intent, subject, predicate, and object.
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When language + root are supplied (from enriched PropositionGraph nodes
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carrying 3-core-language depth), the surface incorporates etymological
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precision for Hebrew (root density) and Koine Greek (Logos precision).
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English base remains unchanged.
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"""
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template = _INTENT_TEMPLATES.get(intent, _INTENT_TEMPLATES[IntentTag.UNKNOWN])
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predicate_h = humanize_predicate(predicate)
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obj_display = obj if obj not in ("<pending>", "<prior>") else "..."
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# Masterful 3-language depth framing on the articulation side.
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# Depth travels with the shared GraphNode from resolve_entry grounding.
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if language and root and language != "en":
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if language == "he":
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depth_note = f" (Hebrew root: {root})"
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elif language in ("grc", "el"):
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depth_note = f" (Koine Greek: {root})"
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else:
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depth_note = f" ({language} root: {root})"
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# For definition-style intents, highlight the term itself.
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# For others, qualify the object referent.
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if intent in (IntentTag.DEFINITION, IntentTag.RECALL, IntentTag.VERIFICATION):
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subject = f"{subject}{depth_note}"
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else:
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obj_display = f"{obj_display}{depth_note}"
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return template.format(
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subject=subject,
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predicate_h=predicate_h,
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obj=obj_display,
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secondary=secondary or obj_display,
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)
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