e5643454d9
Increment 2 for ADR-0252 Track B. Extends Increment 1's structure-mapping slice with pure-family canonicals S2–S4, overlapping-waves selector, and a structure-mapping-owned pure-S1 text extract that recovers four real holdout cases the serving reader misses (0148, 0228, 0234, 0441). Bar results (command-backed via scripts/measure_trackb_inc2.py): - generalization ratio S1 = 9.0 (9 holdout cases / 1 template) - coverage gain organ 5 → trackb 9, wrong=0 - selector routes S1/S2/S3; refuses empty; surface≠structure Off-serving: no organ retirement, serving reader untouched. S2–S4 holdout ratios are 0 (parser frontier). S3/S4 emit refuses at multi-register scope without weakening the three-gate wrong=0 path. [Verification]: Smoke suite passed locally (~132s, 176 passed); trackb unit tests 35 passed; measure_trackb_inc2 all modes green.
106 lines
3.3 KiB
Python
106 lines
3.3 KiB
Python
"""Overlapping-waves selector (ADR-0252 stage 5 / revive ADR-0174).
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Given a role-graph, hold candidate canonical mappings, rank them, pick the
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best, **refuse on ambiguity/tie**, and suppress surface-similarity as the
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decision driver (structure predicates only).
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Blind to gold labels. Deterministic ranking.
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from generate.structure_mapping.mapper import (
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MAPPERS,
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StructureMapRefuse,
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StructureMapResult,
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)
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from generate.structure_mapping.role_predicate import RoleGraph
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# Systematicity / specificity scores: more constraining pure-family matches
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# rank higher. Ties at the same score → refuse.
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_FAMILY_SCORE: dict[str, int] = {
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# Multi-predicate pure families outrank single-predicate ones.
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"S1": 30, # compare + contain + total
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"S4": 30, # compare_add + contain + total
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"S2": 25, # transfer + 2 contains
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"S3": 10, # single rate
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}
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@dataclass(frozen=True, slots=True)
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class SelectorResult:
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"""Selected canonical mapping, or a refuse with diagnostics."""
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selected: StructureMapResult | None
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refused: bool
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reason: str | None
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candidates: tuple[StructureMapResult, ...]
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refused_families: tuple[tuple[str, str], ...]
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"""(structure_id, refuse_reason) for families that did not match."""
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def select_structure(
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role_graph: RoleGraph,
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*,
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families: tuple[str, ...] = ("S1", "S2", "S3", "S4"),
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) -> SelectorResult:
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"""Rank pure-family mappers; pick unique best; refuse on empty or tie.
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Surface attributes (entity names, numbers) never affect ranking — only
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which pure-family mappers admit the role graph and their fixed scores.
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"""
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if not isinstance(role_graph, RoleGraph):
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raise TypeError(
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f"select_structure expects RoleGraph, got {type(role_graph).__name__}"
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)
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hits: list[StructureMapResult] = []
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refuses: list[tuple[str, str]] = []
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for fam in families:
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mapper = MAPPERS.get(fam)
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if mapper is None:
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refuses.append((fam, "unknown_family"))
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continue
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out = mapper(role_graph)
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if isinstance(out, StructureMapResult):
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hits.append(out)
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else:
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assert isinstance(out, StructureMapRefuse)
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refuses.append((fam, out.reason))
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if not hits:
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return SelectorResult(
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selected=None,
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refused=True,
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reason="no_family_matched",
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candidates=(),
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refused_families=tuple(refuses),
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)
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# Rank by systematicity score; secondary key = structure_id for stability.
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ranked = sorted(
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hits,
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key=lambda m: (-_FAMILY_SCORE.get(m.structure_id, 0), m.structure_id),
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)
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best = ranked[0]
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best_score = _FAMILY_SCORE.get(best.structure_id, 0)
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tied = [m for m in ranked if _FAMILY_SCORE.get(m.structure_id, 0) == best_score]
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if len(tied) > 1:
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ids = ",".join(sorted(m.structure_id for m in tied))
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return SelectorResult(
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selected=None,
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refused=True,
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reason=f"ambiguous_tie:{ids}",
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candidates=tuple(ranked),
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refused_families=tuple(refuses),
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)
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return SelectorResult(
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selected=best,
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refused=False,
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reason=None,
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candidates=tuple(ranked),
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refused_families=tuple(refuses),
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)
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