Merge pull request #403 from AssetOverflow/feat/matcher-extension-subtractive
feat(matcher-extension/ME-4): subtractive composition matcher
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3 changed files with 418 additions and 0 deletions
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@ -85,6 +85,7 @@ _TEST_SUITES: dict[str, tuple[str, ...]] = {
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"tests/test_me2_cross_sentence_subject.py",
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"tests/test_me2_case_0019_admits.py",
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"tests/test_me3_additive_composition.py",
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"tests/test_me4_subtractive_composition.py",
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),
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"algebra": (
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"tests/test_versor_closure.py",
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@ -1012,6 +1012,16 @@ def _match_multiplicative_aggregation(
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# ME-3 dispatch — same Literal narrowing keeps the return type
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# consistent ('aggregate' is reused).
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return _try_extract_additive_composition_anchor(statement, spec)
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if anchor_kind == "subtractive_quantity_composition":
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# ME-4 dispatch — subtractive shape returns ("amount" intent).
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# Cast the Literal return: the matcher signature widens at the
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# type level to include any 'aggregate'/'amount' but the caller
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# in match() reads graph_intent verbatim.
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sub_result = _try_extract_subtractive_composition_anchor(statement, spec)
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if sub_result is None:
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return None
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anchors, _ = sub_result
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return (anchors, "aggregate") # reuse 'aggregate' label for subtractive too
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if anchor_kind != "multiplicative_aggregate":
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return None
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padded = _padded_lower(statement)
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@ -1184,6 +1194,156 @@ _ADDITIVE_COMPOSITION_VERBS: Final[frozenset[str]] = frozenset({
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})
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# ---------------------------------------------------------------------------
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# ME-4 — subtractive composition matcher.
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#
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# Admits "<Subject> <init-verb> <N> <unit>(,| then|; etc.) <sub-verb>
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# <M> <unit>" (same unit; positive initial verb followed by removal
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# verb) and emits a pre-composed CandidateInitial(N - M, unit).
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#
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# Refusal-preferring discipline: count_b >= count_a → refuse
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# (non-negative remainder; subtractive composition that goes below
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# zero is a wrong>0 hazard).
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# ---------------------------------------------------------------------------
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_SUBTRACTIVE_TWO_QUANTITY_RE: Final[re.Pattern[str]] = re.compile(
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r"""(?ix)
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^\s*
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(?P<subject>[A-Z][a-zA-Z]+)
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\s+
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(?P<verb_a>had|has|got|owns|owned|earned|saved|made|received|bought)
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\s+
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(?P<count_a>\d+(?:\.\d+)?)
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\s+
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(?P<unit_a>[a-z]+)
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\s*
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(?:,|\sthen\s|;|\s+and\s+then\s+|\s+then\s+|\s+and\s+)
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\s*
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(?:then\s+)?
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(?P<verb_b>lost|spent|gave|donated|paid|removed|sold|used|consumed)
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(?:\s+away)?
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\s+
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(?P<count_b>\d+(?:\.\d+)?)
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\s+
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(?P<unit_b>[a-z]+)
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\b
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""",
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)
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_SUBTRACTIVE_COMPOSITION_SHAPE: Final[str] = "bound(initial) − bound(removed)"
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_SUBTRACTIVE_INITIAL_VERBS: Final[frozenset[str]] = frozenset({
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"had", "has", "got", "owns", "owned", "earned", "saved",
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"made", "received", "bought",
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})
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_SUBTRACTIVE_REMOVAL_VERBS: Final[frozenset[str]] = frozenset({
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"lost", "spent", "gave", "donated", "paid", "removed",
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"sold", "used", "consumed",
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})
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def _try_extract_subtractive_composition_anchor(
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statement: str, spec: Mapping[str, Any]
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) -> tuple[tuple[Mapping[str, Any], ...], Literal["amount"]] | None:
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"""Extract a pre-composed CandidateInitial for subtractive composition.
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See module docstring above for narrowness layers. ``count_b >=
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count_a`` refuses (non-negative remainder discipline; wrong>0
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hazard).
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"""
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if spec.get("anchor_kind") != "subtractive_quantity_composition":
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return None
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observed_units = set(spec.get("observed_units") or ())
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if not observed_units:
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return None
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matches = list(_SUBTRACTIVE_TWO_QUANTITY_RE.finditer(statement))
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if len(matches) != 1:
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return None
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m = matches[0]
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subject = m.group("subject")
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if subject.lower() in _REFUSED_SUBJECT_TOKENS:
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return None
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if subject.lower() in _COMMON_DETERMINERS_AT_HEAD:
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return None
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verb_a = m.group("verb_a").lower()
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verb_b = m.group("verb_b").lower()
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if verb_a not in _SUBTRACTIVE_INITIAL_VERBS:
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return None
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if verb_b not in _SUBTRACTIVE_REMOVAL_VERBS:
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return None
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unit_a = m.group("unit_a").lower()
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unit_b = m.group("unit_b").lower()
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if unit_a.rstrip("s") != unit_b.rstrip("s"):
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return None
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canonical_unit = unit_a
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if (
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canonical_unit not in observed_units
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and canonical_unit.rstrip("s") not in observed_units
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):
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return None
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count_a_token = m.group("count_a")
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count_b_token = m.group("count_b")
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try:
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count_a = float(count_a_token)
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count_b = float(count_b_token)
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except ValueError:
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return None
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if count_a <= 0 or count_b <= 0:
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return None
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if count_b >= count_a:
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return None # Non-negative remainder; wrong>0 hazard.
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composed_value_f = count_a - count_b
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composed_value: int | float
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if (
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composed_value_f.is_integer()
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and "." not in count_a_token
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and "." not in count_b_token
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):
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composed_value = int(composed_value_f)
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else:
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composed_value = composed_value_f
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from generate.math_candidate_parser import CandidateInitial
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from generate.math_problem_graph import InitialPossession, Quantity
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matched_anchor = verb_a if verb_a in {
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"has", "had", "saved", "earned", "got", "received", "bought", "made", "paid",
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} else "had"
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composed_initial = CandidateInitial(
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initial=InitialPossession(
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entity=subject,
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quantity=Quantity(value=composed_value, unit=canonical_unit),
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),
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source_span=m.group(0),
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matched_anchor=matched_anchor,
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matched_value_token=str(composed_value),
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matched_unit_token=canonical_unit,
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matched_entity_token=subject,
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)
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anchor: Mapping[str, Any] = {
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"kind": "subtractive_quantity_composition",
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"composition_shape": _SUBTRACTIVE_COMPOSITION_SHAPE,
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"composed_initial": composed_initial,
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"count_a": count_a_token,
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"count_b": count_b_token,
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"unit": canonical_unit,
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"subject": subject,
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"initial_verb": verb_a,
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"removal_verb": verb_b,
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}
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return ((anchor,), "amount")
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def _match_currency_amount(
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statement: str, spec: Mapping[str, Any]
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) -> tuple[tuple[Mapping[str, Any], ...], Literal["amount"]] | None:
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257
tests/test_me4_subtractive_composition.py
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257
tests/test_me4_subtractive_composition.py
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@ -0,0 +1,257 @@
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"""ME-4 — subtractive composition matcher tests.
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Covers the ``subtractive_quantity_composition`` extension to
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``_match_multiplicative_aggregation``. Pattern: ``<Subject> <init-verb>
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<N> <unit>(,| then| ;| and then| and) <sub-verb> <M> <unit>`` with
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same unit and ``M < N`` (non-negative remainder discipline).
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"""
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from __future__ import annotations
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import json
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from pathlib import Path
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from typing import Any, Mapping
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from evals.refusal_taxonomy.shape_categories import ShapeCategory
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from generate.comprehension.composition_registry import (
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clear_cache as clear_composition_cache,
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)
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from generate.math_candidate_parser import CandidateInitial
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from generate.recognizer_anchor_inject import inject_from_match
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from generate.recognizer_match import (
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RecognizerMatch,
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_match_multiplicative_aggregation,
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)
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from language_packs.compile_compositions import compile_compositions
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_SPEC: Mapping[str, Any] = {
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"anchor_kind": "subtractive_quantity_composition",
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"observed_units": ["apples", "apple", "dollars", "pounds", "pound", "books"],
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}
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_SHAPE = "bound(initial) − bound(removed)"
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def setup_function(_):
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clear_composition_cache()
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def test_canonical_subtractive_admits():
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result = _match_multiplicative_aggregation(
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"Sam had 50 apples, gave 20 apples.", _SPEC
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)
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assert result is not None
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a = result[0][0]
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assert a["composition_shape"] == _SHAPE
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assert a["subject"] == "Sam"
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composed = a["composed_initial"]
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assert isinstance(composed, CandidateInitial)
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assert composed.initial.entity == "Sam"
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assert composed.initial.quantity.value == 30
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assert composed.initial.quantity.unit == "apples"
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def test_then_connective_admits():
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result = _match_multiplicative_aggregation(
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"Mark had 100 dollars then spent 30 dollars.", _SPEC
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)
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assert result is not None
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assert result[0][0]["composed_initial"].initial.quantity.value == 70
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def test_and_connective_admits():
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result = _match_multiplicative_aggregation(
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"Tom had 10 apples and lost 4 apples.", _SPEC
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)
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assert result is not None
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assert result[0][0]["composed_initial"].initial.quantity.value == 6
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def test_negative_remainder_refuses():
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"""Refusal-preferring: count_b >= count_a is the wrong>0 hazard."""
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result = _match_multiplicative_aggregation(
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"Lily had 5 apples and lost 10 apples.", _SPEC
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)
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assert result is None
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def test_equal_remainder_refuses():
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result = _match_multiplicative_aggregation(
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"Lily had 5 apples and lost 5 apples.", _SPEC
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)
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assert result is None # zero remainder still refuses (initial=0 boundary)
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def test_pronoun_subject_refuses():
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result = _match_multiplicative_aggregation(
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"He had 10 apples, gave 3 apples.", _SPEC
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)
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assert result is None
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def test_determiner_subject_refuses():
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result = _match_multiplicative_aggregation(
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"The cat had 10 apples, gave 3 apples.", _SPEC
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)
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assert result is None
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def test_cross_unit_refuses():
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result = _match_multiplicative_aggregation(
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"Sam had 50 apples, gave 20 dollars.", _SPEC
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)
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assert result is None
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def test_unobserved_unit_refuses():
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spec = dict(_SPEC)
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spec["observed_units"] = ["dollars"]
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result = _match_multiplicative_aggregation(
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"Sam had 50 apples, gave 20 apples.", spec
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)
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assert result is None
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def test_unknown_initial_verb_refuses():
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result = _match_multiplicative_aggregation(
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"Sam adopted 50 apples, gave 20 apples.", _SPEC
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)
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assert result is None
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def test_unknown_removal_verb_refuses():
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result = _match_multiplicative_aggregation(
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"Sam had 50 apples, dropped 20 apples.", _SPEC
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)
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assert result is None # 'dropped' not in removal verb set
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def test_gave_away_variant():
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result = _match_multiplicative_aggregation(
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"Sam had 50 apples, gave away 20 apples.", _SPEC
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)
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assert result is not None
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assert result[0][0]["composed_initial"].initial.quantity.value == 30
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def test_additive_path_unaffected():
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"""ME-3 additive dispatch still works."""
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additive_spec = {
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"anchor_kind": "additive_quantity_composition",
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"observed_units": ["dollars"],
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}
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result = _match_multiplicative_aggregation(
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"Maria saved 30 dollars in May and 20 dollars in June.", additive_spec
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)
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assert result is not None
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assert result[0][0]["composed_initial"].initial.quantity.value == 50
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def test_multiplicative_aggregate_path_unaffected():
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spec = {"anchor_kind": "multiplicative_aggregate"}
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result = _match_multiplicative_aggregation(
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"There are 3 bags with 5 items each.", spec
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)
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assert result is not None
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anchors, intent = result
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assert intent == "aggregate"
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assert anchors == ()
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def test_anchor_audit_fields():
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result = _match_multiplicative_aggregation(
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"Sam had 50 apples, gave 20 apples.", _SPEC
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)
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assert result is not None
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a = result[0][0]
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assert {
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"composition_shape",
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"composed_initial",
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"count_a",
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"count_b",
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"unit",
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"subject",
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"initial_verb",
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"removal_verb",
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"kind",
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}.issubset(a.keys())
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# ---------------------------------------------------------------------------
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# End-to-end via composition_registry.
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# ---------------------------------------------------------------------------
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def _stage_pack(tmp_path: Path, polarity: str = "affirms") -> Path:
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pack = tmp_path / "en_core_math_v1"
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comp_dir = pack / "compositions"
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comp_dir.mkdir(parents=True)
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(comp_dir / "subtractive_composition.jsonl").write_text(
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json.dumps(
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{
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"surface_pattern": _SHAPE,
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"composition_category": "subtractive_composition",
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"polarity": polarity,
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"provenance": "test_me4",
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"evidence_hashes": [],
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}
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)
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+ "\n",
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encoding="utf-8",
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)
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_, sha = compile_compositions(pack)
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(pack / "manifest.json").write_text(
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json.dumps(
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{
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"pack_id": "en_core_math_v1",
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"checksum": "x",
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"composition_checksum": sha,
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}
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),
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encoding="utf-8",
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)
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return pack
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def _patch_pack_root(monkeypatch, pack_path: Path) -> None:
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from generate.comprehension import composition_registry as cr
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monkeypatch.setattr(cr, "_DEFAULT_PACK_RELPATH", pack_path)
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monkeypatch.setattr(cr, "_repo_root", lambda: Path("/"))
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def _make_match(anchors):
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class _R:
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spec_id = "test_me4"
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return RecognizerMatch(
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recognizer=_R(), # type: ignore[arg-type]
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category=ShapeCategory.MULTIPLICATIVE_AGGREGATION,
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outcome="admissible",
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graph_intent="aggregate",
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parsed_anchors=anchors,
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)
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def test_end_to_end_subtractive_admits(monkeypatch, tmp_path):
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pack = _stage_pack(tmp_path)
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_patch_pack_root(monkeypatch, pack)
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statement = "Sam had 50 apples, gave 20 apples."
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result = _match_multiplicative_aggregation(statement, _SPEC)
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assert result is not None
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emissions = inject_from_match(_make_match(result[0]), statement)
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assert len(emissions) == 1
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assert emissions[0].initial.quantity.value == 30
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def test_end_to_end_falsifies_suppresses(monkeypatch, tmp_path):
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pack = _stage_pack(tmp_path, polarity="falsifies")
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_patch_pack_root(monkeypatch, pack)
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statement = "Sam had 50 apples, gave 20 apples."
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result = _match_multiplicative_aggregation(statement, _SPEC)
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assert result is not None
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emissions = inject_from_match(_make_match(result[0]), statement)
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assert emissions == ()
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