4ecc17c5ec
MS-1 of multi-step composition. Turns the question into a Target = what the problem asks for, the search's pruning signal + stopping criterion (MS-3). Lexeme-level only (ADR-0165): the existing question parser returns nothing on these GSM8K questions, and 0165 forbids new question-shape grammar regex. Three robust signals: - quantities: numbers stated IN the question (0033's 'when she is 25') via the body's lexeme extractor — they participate in the derivation. - aggregation: presence of an aggregation lexeme (total/altogether/combined/sum/ 'in all'/'in total') — soft hint the final step is a sum. - units: asked units resolved by INTERSECTION with the body's known units (precise lexeme match, e.g. 'jumping'). Superordinates (weight<->pounds) are NOT faked — deferred to a curated superordinate-units pack; until then the unit signal is precise-but-incomplete and the search leans on completeness. Refuse-preferring: empty target field is not an error, just a weaker prune. generate/derivation/target.py: Target + extract_target(question, known_units=()). 12 MS-1 tests (question-quantity, aggregation, body-unit intersection, superordinate-not-faked, determinism, frozen). Verified: derivation suite 57/57; ruff clean; smoke 67. Not wired into serving (Target ready for MS-2/MS-3).
41 lines
1.2 KiB
Python
41 lines
1.2 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.comparatives import (
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ComparativeScalar,
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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.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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"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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"extract_comparative_scalars",
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"extract_quantities",
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"extract_target",
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"search_multiplicative",
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"select_self_verified",
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"self_verifies",
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]
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