PR-6d adds the partition frame: combine all parts into a total, then split that total equally into N containers. r1-06-subtotal-reused moves refused → correct — the FIRST case where the divisor applies to a DERIVED symbol (the total), not a directly given fact. That is real progress toward GSM8K setup comprehension, where intermediate quantities are the norm. Scope (kept narrow on purpose): No new relation kind. No new arithmetic operation. No rational support. No rounding/flooring. No serving path touched. The frame reuses the already-ratified pieces — SumOf(parts) + Div(Symbol(total), Literal(N)) → divide_by — so this PR is reader-only (no IR / admissibility / oracle / signature change). Frame grammar: "They combine their <unit> and split them equally into N <containers>." + "How many <unit> are in each <container>?" -> total = sum(all facts); per_<container> = total / N; ask per_<container>. wrong=0 boundaries: - Exact-divisibility still gates the ANSWER, now over a derived total: 5+6=11, 11/3 is non-exact -> the setup reads correctly but the answer REFUSES (never floors). Setup comprehension and answer exactness are cleanly separated. - Partition/query coherence: a partition is read ONLY together with its "in each <container>" query (and vice versa); container mismatch (box vs jar) refuses. Prevents over-reading a story detail into an unused derived value. Meaningful-fail verified: disabling the guard makes a dangling partition wrongly comprehend. Gates: R1 setup: 4 correct / 0 wrong / 6 refused R1 answers: 4 correct / 0 wrong / 6 refused / setup_wrong 0 / gold_error 0 15-case setup: 15 / 0 / 0 97 PR-6d tests + 99 relational/invariant tests green. Reader is off-serving (no generate.derivation / core.reliability_gate import).
528 lines
20 KiB
Python
528 lines
20 KiB
Python
"""Arithmetic word-problem comprehension -> binding_graph (Phase 2b, domain 5).
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The doctrine-aligned quantity reader, and the binding-graph's FIRST comprehension
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consumer. Quantities live in the ``binding_graph`` substrate — CLAUDE.md: the
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``MeaningGraph`` deliberately excludes quantities — so this reader lives OUTSIDE
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``generate/meaning_graph`` (which stays a numeric-free interlingua, INV-28) and
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targets the binding-graph instead.
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It reads arithmetic prose ("Liam has 6 stickers. Mia has 4 more stickers than
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Liam.") into ``SymbolBinding`` / ``BoundFact`` / ``BoundEquation`` and runs the
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REAL ``check_admissibility`` — there is NO stamped "admitted": an equation is
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admitted only if its operand units actually verify, and a dimensional mismatch
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REFUSES the whole reading. ``to_relational_metric`` then projects the binding-graph
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into the independent ``relational_metric`` oracle for scoring.
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Templates (function-word + order; digits only — a non-digit quantity REFUSES):
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- ``<X> has <N> <unit>`` -> BoundFact(X = N [unit])
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- ``<Y> has <N> more <unit> than <X>`` -> BoundEquation(Y = X + N) op=add
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- ``<Y> has <N> fewer <unit> than <X>`` -> BoundEquation(Y = X - N) op=subtract
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- query ``How many <unit> does <Y> have`` -> ask Y
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- query ``How many <unit> do <X> and <Y> have`` -> total = X + Y; ask total
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Refusal-first: an unparseable clause, a non-digit quantity, a non-identifier name,
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a missing/duplicated query, or an admissibility refusal all return a typed
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``Refusal`` — never a fabricated quantity (wrong=0 at the comprehension layer).
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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 typing import Any
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from generate.binding_graph.admissibility import AdmissibilityError, check_admissibility
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from generate.binding_graph.model import (
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BoundEquation,
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BoundFact,
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BoundUnknown,
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SemanticSymbolicBindingGraph,
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SourceSpanLink,
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SymbolBinding,
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)
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from generate.binding_graph.units import UnitAlgebraError, parse_unit
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from generate.meaning_graph.reader import Refusal, _split_sentences
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from generate.quantitative_expr import (
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Add,
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Div,
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Expr,
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Literal,
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Mul,
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Sub,
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SumOf,
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Symbol,
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dependencies,
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operation_kind,
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to_canonical_string,
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to_relation,
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)
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_INTRODUCED_BY = "comprehend_quantitative"
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#: The generic count dimension for discrete sortal objects (an existing pack
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#: lemma resolving to dimension ``count``). A noun the unit pack does not know is
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#: read as a count of discrete objects, NOT faked into a physical unit.
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_COUNT_UNIT = "item"
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def _resolve_unit(noun: str) -> str:
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"""Map a surface unit noun to a binding-graph unit the pack accepts.
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A KNOWN physical/currency/count unit (``dollars`` -> ``dollar``, ``meters``)
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is used verbatim (``parse_unit`` depluralizes). An UNKNOWN sortal noun
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(``stickers``, ``coins``) is a count of discrete objects -> ``item`` (dimension
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``count``). This keeps admissibility a REAL check: ``count + count`` admits,
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``count + length`` still refuses — nothing is stamped or faked.
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"""
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try:
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parse_unit(noun)
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except UnitAlgebraError:
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return _COUNT_UNIT
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return noun
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@dataclass(frozen=True, slots=True)
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class QuantComprehension:
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"""Successful arithmetic comprehension.
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The question target is no longer a sidecar field — it lives IN the graph as the
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sole :class:`BoundUnknown` (PR-1). Consumers read it via :func:`single_unknown`,
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which refuses (returns ``None``) on a graph that does not carry exactly one
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target rather than silently picking one.
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``equation_exprs`` is the typed expression IR (PR-4) — the reader's SOURCE OF MEANING
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for each equation, as ``(lhs_symbol_id, Expr)`` pairs. ``BoundEquation.rhs_canonical``
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is the serialization of these; the projection reads the IR, never the string.
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"""
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binding_graph: SemanticSymbolicBindingGraph
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equation_exprs: tuple[tuple[str, Expr], ...] = ()
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def single_unknown(graph: SemanticSymbolicBindingGraph) -> BoundUnknown | None:
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"""Return the graph's SOLE question target, or ``None`` if it is not exactly one.
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Zero unknowns (no question) and multiple unknowns (ambiguous target) both REFUSE
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— the caller must not pick one. ``comprehend_quantitative`` always emits exactly
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one; this guards every other construction path (wrong=0 at the consumer boundary).
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"""
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return graph.unknowns[0] if len(graph.unknowns) == 1 else None
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class _QReject(Exception):
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"""Internal: a clause matched a shape but is not honestly readable."""
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def __init__(self, reason: str, detail: str = "") -> None:
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super().__init__(reason)
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self.refusal = Refusal(reason, detail)
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def _ident(tok: str, detail: str) -> str:
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w = tok.strip().lower()
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if not w.isidentifier():
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raise _QReject("non_identifier_name", detail)
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return w
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def _int(tok: str, detail: str) -> int:
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if not tok.isdigit():
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raise _QReject("non_digit_quantity", detail)
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return int(tok)
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@dataclass(frozen=True, slots=True)
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class _Fact:
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entity: str
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value: int
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unit: str
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@dataclass(frozen=True, slots=True)
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class _Eq:
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entity: str
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ref: str
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delta: int
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op: str # "add" | "subtract"
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unit: str
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@dataclass(frozen=True, slots=True)
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class _Mul:
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"""Multiplicative comparative: entity = factor * ref (R1)."""
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entity: str
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ref: str
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factor: int
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unit: str
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@dataclass(frozen=True, slots=True)
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class _Div:
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"""Divisive comparative: entity = ref / divisor (R1, "half as many"). The
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divisor is a dimensionless integer literal; the quotient keeps ref's unit."""
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entity: str
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ref: str
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divisor: int
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unit: str
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@dataclass(frozen=True, slots=True)
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class _Partition:
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"""Aggregate-then-divide: combine all facts into a ``total`` then split that total
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equally into ``divisor`` parts (R1, "They combine their X and split them equally
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into N boxes"). The semantic source is equal PARTITION; the mathematical setup is
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``total = sum(facts)`` + ``per_<container> = total / divisor`` — reusing ``SumOf`` +
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``Div(Symbol, Literal)``, NO new relation kind (the divisor is exact integer
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division, the same wrong=0 boundary as PR-6c)."""
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unit: str # the unit combined and split (hats -> item)
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divisor: int # number of equal parts (3 boxes)
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container: str # SINGULAR container noun (box) — must match the perquery's
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def _singular(noun: str) -> str:
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"""Conservative singularization for container nouns (``boxes`` -> ``box``,
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``bags`` -> ``bag``); already-singular nouns (``box``) pass through unchanged.
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Used ONLY to canonicalize the partition container so the "split into N boxes"
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sentence and the "in each box" query name the same ``per_<container>`` symbol.
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"""
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if noun.endswith("es") and noun[:-2].endswith(("x", "s", "z", "ch", "sh")):
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return noun[:-2]
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if noun.endswith("s") and len(noun) > 1:
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return noun[:-1]
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return noun
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#: Word factors for "twice/double/triple ... as many" (a multiply by a dimensionless int).
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_FACTOR_WORDS: dict[str, int] = {"twice": 2, "double": 2, "triple": 3, "quadruple": 4}
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#: Word divisors for "half ... as many" (a divide by a dimensionless int). The divisive
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#: twin of ``_FACTOR_WORDS``; both slot into the same 8-token "<WORD> as many" template.
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#: 'third'/'quarter' (non-power-of-two surface forms with an article) are deferred.
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_DIVISOR_WORDS: dict[str, int] = {"half": 2}
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def _try_multiplicative(entity: str, toks: list[str], detail: str) -> "_Mul | _Div | None":
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"""Match the comparative templates → ``_Mul`` (multiply) or ``_Div`` (divide).
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- "Y has <factor-word> as many <unit> as X" → ``_Mul`` (twice/double/triple/quadruple)
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- "Y has <divisor-word> as many <unit> as X" → ``_Div`` (half)
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- "Y has <N> times as many <unit> as X" → ``_Mul``
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Returns None if the clause is not comparative (the caller then tries the digit-led
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fact/additive templates)."""
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# [Y, has, WORD, as, many, UNIT, as, X] — factor and divisor words share this shape.
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if (
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len(toks) == 8
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and toks[3] == "as"
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and toks[4] == "many"
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and toks[6] == "as"
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):
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ref = _ident(toks[7], detail)
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unit = _resolve_unit(_ident(toks[5], detail))
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if toks[2] in _FACTOR_WORDS:
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return _Mul(entity, ref, _FACTOR_WORDS[toks[2]], unit)
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if toks[2] in _DIVISOR_WORDS:
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return _Div(entity, ref, _DIVISOR_WORDS[toks[2]], unit)
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# [Y, has, N, times, as, many, UNIT, as, X]
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if (
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len(toks) == 9
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and toks[2].isdigit()
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and toks[3] == "times"
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and toks[4] == "as"
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and toks[5] == "many"
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and toks[7] == "as"
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):
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return _Mul(entity, _ident(toks[8], detail), int(toks[2]),
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_resolve_unit(_ident(toks[6], detail)))
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return None
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def _parse_sentence(body: str, detail: str):
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"""Return a (_Fact | _Eq | _Mul | ('query', entity, unit) | ('sumquery', parts, unit))
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spec, or None if the sentence matches no arithmetic template."""
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toks = body.strip().lower().rstrip("?.!").split()
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if not toks:
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return None
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if len(toks) >= 5 and toks[0] == "how" and toks[1] == "many":
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unit = _resolve_unit(_ident(toks[2], detail))
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# "How many <unit> are in each <container>?" -> the partition per-container target.
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if len(toks) == 7 and toks[3] == "are" and toks[4] == "in" and toks[5] == "each":
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return ("perquery", _singular(_ident(toks[6], detail)), unit)
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if toks[-1] == "have":
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rest = toks[3:-1] # between "<unit>" and "have"
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if rest and rest[0] == "does" and len(rest) == 2:
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return ("query", _ident(rest[1], detail), unit)
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if rest and rest[0] == "do":
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parts = [_ident(t, detail) for t in rest[1:] if t != "and"]
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if len(parts) >= 2:
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return ("sumquery", tuple(parts), unit)
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raise _QReject("unreadable_quantity_query", detail)
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# Partition: "They combine their <unit> and split them equally into <N> <container>."
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if (
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len(toks) == 11
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and toks[0] == "they"
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and toks[1] == "combine"
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and toks[2] == "their"
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and toks[4] == "and"
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and toks[5] == "split"
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and toks[6] == "them"
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and toks[7] == "equally"
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and toks[8] == "into"
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and toks[9].isdigit()
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):
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return _Partition(
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unit=_resolve_unit(_ident(toks[3], detail)),
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divisor=_int(toks[9], detail),
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container=_singular(_ident(toks[10], detail)),
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)
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if len(toks) >= 4 and toks[1] == "has":
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entity = _ident(toks[0], detail)
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# Multiplicative comparative is checked BEFORE the digit gate (its factor may be
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# a word like "twice", which is not a digit).
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mul = _try_multiplicative(entity, toks, detail)
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if mul is not None:
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return mul
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value = _int(toks[2], detail)
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if len(toks) == 4:
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return _Fact(entity, value, _resolve_unit(_ident(toks[3], detail)))
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if len(toks) == 7 and toks[3] in ("more", "fewer") and toks[5] == "than":
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op = "add" if toks[3] == "more" else "subtract"
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return _Eq(
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entity, _ident(toks[6], detail), value, op, _resolve_unit(_ident(toks[4], detail))
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)
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raise _QReject("unreadable_quantity_clause", detail)
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return None
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def _span(text: str) -> SourceSpanLink:
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return SourceSpanLink(source_id="input", start=0, end=max(1, len(text)), text=text or " ")
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def comprehend_quantitative(text: str, source_id: str = "input") -> QuantComprehension | Refusal:
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"""Comprehend arithmetic prose into a binding_graph + asked entity, or refuse."""
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if not text or not text.strip():
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return Refusal("empty")
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sentences = _split_sentences(text)
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if not sentences:
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return Refusal("empty")
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facts: list[_Fact] = []
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eqs: list[_Eq] = []
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muls: list[_Mul] = []
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divs: list[_Div] = []
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partitions: list[_Partition] = []
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queries: list[tuple] = []
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try:
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for body, _terminator, _start, _end in sentences:
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spec = _parse_sentence(body, body)
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if spec is None:
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return Refusal("no_quantity_template", body)
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if isinstance(spec, _Fact):
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facts.append(spec)
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elif isinstance(spec, _Eq):
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eqs.append(spec)
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elif isinstance(spec, _Mul):
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muls.append(spec)
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elif isinstance(spec, _Div):
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divs.append(spec)
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elif isinstance(spec, _Partition):
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partitions.append(spec)
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else:
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queries.append(spec)
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except _QReject as rej:
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return rej.refusal
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if len(queries) != 1 or not facts:
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return Refusal("no_single_quantity_query")
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if len(partitions) > 1:
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return Refusal("multiple_partitions")
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partition = partitions[0] if partitions else None
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unit_of: dict[str, str] = {}
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role_of: dict[str, str] = {}
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for f in facts:
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unit_of[f.entity], role_of[f.entity] = f.unit, "count"
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for e in eqs:
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unit_of[e.entity], role_of[e.entity] = e.unit, "count"
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for m in muls:
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unit_of[m.entity], role_of[m.entity] = m.unit, "count"
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for d in divs:
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unit_of[d.entity], role_of[d.entity] = d.unit, "count"
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query = queries[0]
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# A partition is read ONLY together with its "in each <container>" query, and vice
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# versa — a partition without that target, or that target without a partition, refuses.
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if (partition is not None) != (query[0] == "perquery"):
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return Refusal("partition_query_mismatch")
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sum_eq: tuple[str, tuple[str, ...]] | None = None
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partition_eq: tuple[str, str, int] | None = None # (per_box, total, divisor)
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if query[0] == "query":
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ask_entity, ask_unit = query[1], query[2]
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elif query[0] == "perquery":
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# Aggregate-then-divide: total = sum(all facts); per_<container> = total / divisor.
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container, ask_unit = query[1], query[2]
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assert partition is not None # guaranteed by the mismatch guard above
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if partition.container != container:
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return Refusal("partition_container_mismatch")
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ask_entity = "per_" + container
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unit_of.setdefault("total", partition.unit)
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role_of["total"] = "total"
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unit_of.setdefault(ask_entity, partition.unit)
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role_of[ask_entity] = "count"
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sum_eq = ("total", tuple(f.entity for f in facts))
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partition_eq = (ask_entity, "total", partition.divisor)
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else: # sumquery -> synthesize a total symbol + sum equation
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parts, ask_unit = query[1], query[2]
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ask_entity = "total"
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unit_of.setdefault(ask_entity, ask_unit)
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role_of[ask_entity] = "total"
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sum_eq = (ask_entity, parts)
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referenced: set[str] = set()
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for f in facts:
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referenced.add(f.entity)
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for e in eqs:
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referenced.update((e.entity, e.ref))
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for m in muls:
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referenced.update((m.entity, m.ref))
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for d in divs:
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referenced.update((d.entity, d.ref))
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if sum_eq is not None:
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referenced.add(sum_eq[0])
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referenced.update(sum_eq[1])
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if partition_eq is not None:
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referenced.add(partition_eq[0])
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referenced.add(partition_eq[1])
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referenced.add(ask_entity)
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symbols = [
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SymbolBinding(
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symbol_id=sid,
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name=sid,
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semantic_role=role_of.get(sid, "count"),
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source_span=_span(sid),
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introduced_by=_INTRODUCED_BY,
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entity=sid,
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unit=unit_of.get(sid),
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)
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for sid in sorted(referenced)
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]
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symbols_by_id = {s.symbol_id: s for s in symbols}
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bound_facts = tuple(
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BoundFact(symbol_id=f.entity, value=str(f.value), source_span=_span(f.entity), unit=f.unit)
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for f in facts
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)
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# The typed expression IR (PR-4) is the SOURCE OF MEANING; rhs_canonical / dependencies
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# / operation_kind are all derived from it, never recovered by re-parsing the string.
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expr_specs: list[tuple[str, Expr]] = [
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(e.entity, (Add if e.op == "add" else Sub)(Symbol(e.ref), Literal(e.delta)))
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for e in eqs
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]
|
|
expr_specs.extend(
|
|
(m.entity, Mul(Symbol(m.ref), Literal(m.factor))) for m in muls
|
|
)
|
|
expr_specs.extend(
|
|
(d.entity, Div(Symbol(d.ref), Literal(d.divisor))) for d in divs
|
|
)
|
|
if sum_eq is not None:
|
|
lhs, parts = sum_eq
|
|
expr_specs.append((lhs, SumOf(tuple(Symbol(p) for p in parts))))
|
|
# The partition divide is appended AFTER the sum so ``total`` is forward-resolved
|
|
# before ``per_<container> = total / divisor`` (the oracle substitutes in this order).
|
|
if partition_eq is not None:
|
|
lhs, ref, divisor = partition_eq
|
|
expr_specs.append((lhs, Div(Symbol(ref), Literal(divisor))))
|
|
|
|
# equations: shell -> REAL admissibility -> rebuild (NEVER stamp "admitted").
|
|
equations: list[BoundEquation] = []
|
|
for lhs, expr in expr_specs:
|
|
rhs = to_canonical_string(expr)
|
|
deps = dependencies(expr)
|
|
op = operation_kind(expr)
|
|
shell = BoundEquation(
|
|
lhs_symbol_id=lhs,
|
|
rhs_canonical=rhs,
|
|
dependencies=deps,
|
|
operation_kind=op,
|
|
unit_proof="pending",
|
|
admissibility_status="pending",
|
|
source_span=_span(lhs),
|
|
)
|
|
try:
|
|
proof = check_admissibility(shell, symbols=symbols_by_id)
|
|
except AdmissibilityError as exc:
|
|
return Refusal("admissibility_refused", f"{lhs}: {exc.reason}")
|
|
equations.append(
|
|
BoundEquation(
|
|
lhs_symbol_id=lhs,
|
|
rhs_canonical=rhs,
|
|
dependencies=deps,
|
|
operation_kind=op,
|
|
unit_proof=proof.to_canonical_string(),
|
|
admissibility_status="admitted",
|
|
source_span=_span(lhs),
|
|
)
|
|
)
|
|
|
|
# The question target lives INSIDE the graph (ADR-0135): a BoundUnknown bound to
|
|
# the asked symbol at the terminal state. The form is "total" for an aggregate
|
|
# query ("how many do X and Y have"), else "count". ``query`` is retained as a
|
|
# consistent-by-construction convenience for the existing relational_metric
|
|
# projection + realize path; a follow-up collapses it onto graph.unknowns.
|
|
unknown = BoundUnknown(
|
|
symbol_id=ask_entity,
|
|
question_span=_span(ask_entity),
|
|
state_index="terminal",
|
|
question_form="total" if sum_eq is not None else "count",
|
|
expected_unit=ask_unit,
|
|
)
|
|
|
|
try:
|
|
graph = SemanticSymbolicBindingGraph(
|
|
symbols=tuple(symbols),
|
|
facts=bound_facts,
|
|
equations=tuple(equations),
|
|
unknowns=(unknown,),
|
|
)
|
|
except Exception as exc: # noqa: BLE001 — surface construction refusal
|
|
return Refusal("invalid_binding_graph", repr(exc))
|
|
|
|
return QuantComprehension(binding_graph=graph, equation_exprs=tuple(expr_specs))
|
|
|
|
|
|
def to_relational_metric(
|
|
comp: QuantComprehension,
|
|
) -> tuple[list[dict[str, Any]], dict[str, Any]] | None:
|
|
"""Project the comprehension into ``(relations, query)`` for
|
|
``evals.relational_metric.oracle.oracle_answer``.
|
|
|
|
Reads the typed expression IR (``comp.equation_exprs``) directly — meaning is NEVER
|
|
recovered by re-parsing ``rhs_canonical`` (PR-4). Facts are emitted before equations
|
|
and equations in dependency order, so the oracle's forward substitution never hits an
|
|
unresolved reference. A relation shape the projection does not handle REFUSES.
|
|
"""
|
|
graph = comp.binding_graph
|
|
relations: list[dict[str, Any]] = [
|
|
{"kind": "fact", "entity": f.symbol_id, "value": int(f.value)} for f in graph.facts
|
|
]
|
|
for lhs, expr in comp.equation_exprs:
|
|
rel = to_relation(lhs, expr)
|
|
if rel is None:
|
|
return None # unhandled equation shape -> refuse
|
|
relations.append(rel)
|
|
if not relations:
|
|
return None
|
|
target = single_unknown(graph)
|
|
if target is None:
|
|
return None # no/ambiguous question target -> refuse (never pick one)
|
|
return relations, {"entity": target.symbol_id, "unit": target.expected_unit}
|