6611a7017d
The first cross-clause comprehension reading: one actor's quantity changes over
successive clauses ("Sam has 14 apples. He buys 9 more." -> 14 + 9). It is the
safe specialisation of the cross-clause sum that GB-3a refuses wholesale (the
Alice/Tom hazard) — we chain only when (same referent) AND (a licensed change
cue of unambiguous polarity), else refuse.
generate/derivation/accumulate.py — compose_accumulation:
- anchor on clause 1's single quantity; apply +M (gain) / -M (loss) per later
change clause, operand taken in the anchor's unit (accumulation is same-dimension);
routed through the unchanged self-verification gate.
- polarity (ordered, so ambiguous "gives" is resolved not guessed): "more" -> gain;
else unambiguous loss verb -> loss; else gives/gave + to/away -> loss; else
unambiguous gain verb -> gain; else REFUSE.
- referent guard (the ADR-0174 multi-actor hazard's defensive fix, built minimally
in the clean lane — NOT the retired gender-blind resolver): a later clause's
subject token must be a pronoun or the anchor's name; a NEW named subject (Tom)
-> refuse. Pronoun gender/number is not matched; a new name is the only signal.
evals/.../accumulation_runner.py — practice scorer: on a base refusal, attempt
compose_accumulation and gold-check (mirrors search_runner). Sealed: fires only
on already-refused cases, never alters serving.
Measured (sealed practice additive lane): 0 -> 55 correct, wrong unchanged at 1
(the base scorer's pre-existing one; accumulation added 55 correct, 0 wrong). The
36 still-refused are multi-change (GB-3b.2) or unrecognised verbs (vocab growth) —
conservative, never wrong.
Proof obligations (tests fail under the violation): new-named-actor refuses (H1),
no/ambiguous change cue refuses, list anchor refuses, multi-change refuses,
determinism. 136 targeted tests + architectural invariants green; serving 3/47/0
byte-identical (lane-SHA 8/8, claims --check OK).
57 lines
1.6 KiB
Python
57 lines
1.6 KiB
Python
"""ADR-0175 Phase 3 — grounded derivation search + self-verification gate.
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Phase 3a (this surface): the self-verification gate — grounded operands ∧
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grounded operation cues ∧ unit consistency ∧ uniqueness. The wrong=0-critical
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guard that keeps the (Phase 3b) bounded search honest.
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"""
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from __future__ import annotations
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from generate.derivation.clauses import (
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ClauseResult,
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clause_local_results,
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segment_clauses,
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)
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from generate.derivation.accumulate import compose_accumulation
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from generate.derivation.compose import compose_sequential
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from generate.derivation.comparatives import (
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ComparativeScalar,
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comparative_step,
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extract_comparative_scalars,
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)
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from generate.derivation.extract import extract_quantities
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from generate.derivation.model import GroundedDerivation, Quantity, Step, VALID_OPS
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from generate.derivation.multistep import search_chain
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from generate.derivation.search import MULTIPLICATIVE_CUES, search_multiplicative
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from generate.derivation.target import Target, extract_target
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from generate.derivation.verify import (
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Resolution,
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SelfVerification,
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select_self_verified,
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self_verifies,
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)
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__all__ = [
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"ClauseResult",
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"ComparativeScalar",
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"GroundedDerivation",
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"MULTIPLICATIVE_CUES",
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"Quantity",
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"Resolution",
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"SelfVerification",
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"Step",
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"Target",
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"VALID_OPS",
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"clause_local_results",
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"compose_accumulation",
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"compose_sequential",
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"comparative_step",
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"extract_comparative_scalars",
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"extract_quantities",
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"extract_target",
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"search_chain",
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"search_multiplicative",
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"segment_clauses",
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"select_self_verified",
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"self_verifies",
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]
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