CP-2a populates the CP-1 ledger from gold-labelled candidate readings and reports per-pattern reliability — the measurement the cue-precision thesis rests on. Plus the function-word unit filter, whose value this measurement makes concrete (clean unit_shape labelling). What landed (all sealed; serving 3/47/0 byte-identical): - generate/cue_precision/trainer.py — train_from_cases(cases, enumerators): folds gold-labelled candidate chains into the ledger via record_case. Decoupled (the candidate enumerators are injected, so the package still imports nothing from search). candidates_for dedupes a reading shared by two enumerators. - generate/derivation/multistep.py — extracted the enumeration half of search_chain into public candidate_chains(problem_text); search_chain now delegates (verified byte-identical: ms3 tests + practice counts unchanged). CP-2 needs the readings the search weighs, not just the one it resolves. - generate/derivation/extract.py — function-word unit filter (_NON_UNIT_WORDS): blanks spurious function-word units ($0.75 each -> "", 3/4 of -> "") that corrupt same-unit detection and unit_shape. Closed lexeme set, ADR-0165-safe. - evals/gsm8k_math/practice/v1/cue_precision_report.py — trains over 200 sealed cases (50 train_sample + 150 ADR-0163-F additive) with the real enumerators and prints the per-pattern reliability table. - tests/test_adr_0177_cp2a_training.py — trainer obligations (credit/dedupe/ determinism/empty) via synthetic enumerators; real-measurement well-formedness; search_chain parity. Load-bearing finding (recorded in ADR-0177): over 200 cases EVERY (cue,op,unit_shape) pattern floors at ~0.0 reliability (best: for-multiply-cross_unit 0.0116 at 2/34). The blunt product/sum-of-all readings are almost always wrong vs gold, so the conservative floor correctly trusts nothing. => CP-2b (trust reliable cues) is blocked on candidate GENERATION, not the ledger: candidate readings must get less crude (clause/referent structure, ADR-0178 GB-3b) before any cue earns reliability. Cue-precision and compositional structure are coupled; structure comes first. Verification: 107 targeted tests green (CP-2a/CP-1/extract/ms3/GB-1/2/3/MS-1/2) + architectural invariants; serving CLAIMS.md sha unchanged; practice 4/1/45 and 0/1/149 unchanged. Inert: trains/reports only, consulted by no search/gate.
217 lines
10 KiB
Python
217 lines
10 KiB
Python
"""ADR-0175 Phase 3b / ADR-0179 — lexeme-level quantity extraction.
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Pulls ``(value, unit, source_token)`` triples from a problem using conservative
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orthographic patterns. Per ADR-0165 these are *lexeme* patterns ("what this
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piece looks like: a number, a unit word") — never grammar templates ("how words
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combine to mean X"). The *combining* is the search's job (search.py / compose.py)
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gated by self-verification, which is refuse-preferring; over-extraction here can
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only cost *refusals*, never a wrong answer.
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ADR-0179 enrichments integrated here (sealed lane only — ``chat/`` does not import
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this module, so none of this can move the serving ``3/47/0``):
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* **EX-1 — word-numbers.** ``"three apples"`` → ``3.0``, including tens-one
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hyphen compounds (``"twenty-four"`` → ``24.0``). Reuses the canonical
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``WORD_NUMBERS`` table from :mod:`generate.math_roundtrip` (single number
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vocabulary). Factor-bearing forms (``half``/``third``/``quarter``) are excluded
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— they read as divisors, not counts.
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* **EX-4 — list-unit inheritance.** In a bare numeric list with the unit stated
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once at the end (``"20, 36, 40 and 50 push-ups"``) the trailing unit attaches
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to every number in the list. Still orthographic: a run of number tokens joined
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by comma/``and`` delimiters, then one unit token. Whether the resulting
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quantities may compose is the gate's decision, not the extractor's.
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* **EX-5 — sentence-final numbers.** A number with no following unit word (end of
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sentence/text or before terminal punctuation) extracts with an empty unit so it
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stays available to the completeness check without inventing a unit lexeme.
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* **Unit hygiene (function-word filter).** When the token after a number is a
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function word (``$0.75 each`` → ``each``, ``$40 to go`` → ``to``, ``3/4 of`` →
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``of``), the single-word unit pattern would tag it as the unit — a spurious unit
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that corrupts same-unit detection (GB-2/GB-3) and CP-1's ``unit_shape``. Such
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units are blanked (empty, like a sentence-final number): the value stays
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grounded, the unit is honestly unknown. Closed lexeme set (``_NON_UNIT_WORDS``),
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not a grammar template (ADR-0165).
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EX-3 (multi-word units) is deliberately **not** integrated. Two distinct traps
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defeat the tightest lookahead-anchored rule the brief admits:
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1. **Connective-crossing** (in
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``docs/handoff/AUDIT-ADR-0179-EX-RECONCILE.md``). The greedy lowercase unit
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span regresses GB-2's same-unit detection (``"6 apples and 4 apples"`` → unit
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``"apples and"``) and does not cleanly recover real multi-word units from
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0024-class text (``"20 jumping jacks on Monday"`` → ``"jumping jacks on"``).
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2. **Postmodifier-adjective tails** (discovered during the Track C redo of
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``docs/handoff/PARALLEL-WORK-PLAN-2026-05-29.md``). Even a *tight*
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``digit + lc word + lc word + (?=clause-terminator)`` rule fires on
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``"25 years old?"`` and produces unit ``"years old"`` instead of
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``"years"`` — regressing
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``tests/test_adr_0176_ms1_question_target.py::TestQuestionQuantities::test_extracts_quantity_stated_in_question``.
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The pattern is endemic: GSM8K cases 0006/0033 and several MS2 chain tests use
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``"X years old"``. Closing it would need a second closed lexeme set (a stop
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list of measurement postmodifiers — ``old``, ``tall``, ``long``, ``wide``,
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``deep``, ``high``, ``away``, ``apart``, ``ago``, …) which the audit did not
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anticipate and which the Track C brief judged too open-ended to enumerate
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responsibly. ``TestEX3StillDeferred`` in
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``tests/test_adr_0179_extract.py`` pins this second trap so no future redo
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silently re-introduces it.
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"""
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from __future__ import annotations
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import re
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from typing import Final
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from generate.derivation.model import Quantity
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from generate.math_roundtrip import WORD_NUMBERS
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# Number (int or decimal) immediately followed by a single unit word. Lexeme-level.
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_QTY_RE: Final[re.Pattern[str]] = re.compile(
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r"(?<![\w.])(\d+(?:\.\d+)?)\s+([a-zA-Z]+)"
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)
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# EX-4: a same-unit numeric list with the unit stated once at the end, e.g.
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# ``20, 36, 40 and 50 push-ups``. A run of number tokens separated by comma/and
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# delimiters, followed by one (optionally hyphenated) unit token.
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_LIST_WITH_TRAILING_UNIT_RE: Final[re.Pattern[str]] = re.compile(
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r"(?<![\w.])"
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r"((?:\d+(?:\.\d+)?\s*(?:,\s*|\s+and\s+)){1,}\d+(?:\.\d+)?)"
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r"\s+([a-zA-Z]+(?:-[a-zA-Z]+)*)"
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)
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_NUMBER_RE: Final[re.Pattern[str]] = re.compile(r"\d+(?:\.\d+)?")
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# EX-1: word-number (optionally a tens-one hyphen compound) followed by a unit
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# word. Built from the round-trip table; factor-bearing forms excluded.
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_WORD_NUMBER_ALT: Final[str] = "|".join(
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re.escape(word)
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for word in sorted(WORD_NUMBERS, key=len, reverse=True)
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if word not in {"half", "third", "quarter"}
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)
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_WORD_QTY_RE: Final[re.Pattern[str]] = re.compile(
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rf"(?i)\b({_WORD_NUMBER_ALT})(?:-({_WORD_NUMBER_ALT}))?\s+([a-zA-Z]+)\b"
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)
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# EX-5: a number with no following unit, at end of sentence/text.
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_FINAL_NUMBER_RE: Final[re.Pattern[str]] = re.compile(
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r"(?<![\w.])(\d+(?:\.\d+)?)(?=\s*(?:[.?!]|$))"
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)
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# Function words that are never units. When the token immediately after a number
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# is one of these (``$0.75 each``, ``$40 to go``, ``3/4 of``), the single-word unit
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# pattern would otherwise tag the function word as the unit — a spurious unit that
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# corrupts same-unit detection (GB-2/GB-3) and CP-1's unit_shape. Emitting an empty
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# unit instead (like a sentence-final number) is honest: the value is grounded, the
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# unit is simply unknown. Closed lexeme set (cf. ``WORD_NUMBERS``); ADR-0165-safe —
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# it names tokens that are not unit nouns, it does not parse sentence structure.
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_NON_UNIT_WORDS: Final[frozenset[str]] = frozenset(
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{
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"a", "an", "the", "of", "to", "for", "in", "on", "at", "as", "than",
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"per", "each", "every", "and", "or", "with", "by", "from", "more",
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"less", "about", "that",
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}
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)
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def _clean_unit(unit: str) -> str:
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"""Lowercase a unit token; blank it if it is a non-unit function word."""
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lowered = unit.lower()
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return "" if lowered in _NON_UNIT_WORDS else lowered
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def _quantity(value_token: str, unit: str) -> Quantity | None:
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"""Build a quantity from an already-matched numeric token."""
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try:
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value = float(value_token)
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except ValueError: # pragma: no cover - regex guarantees numeric
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return None
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return Quantity(value=value, unit=_clean_unit(unit), source_token=value_token)
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def _resolve_word_number(first: str, second: str | None) -> float | None:
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"""Resolve a conservative word-number token from ``WORD_NUMBERS``.
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A bare word resolves directly. A hyphen compound resolves only as a tens-one
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form (``twenty-four``, ``ninety-nine``); anything else returns ``None`` so the
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extractor stays conservative rather than guessing a composition rule.
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"""
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first_value = WORD_NUMBERS.get(first.lower())
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if first_value is None:
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return None
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if second is None:
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return float(first_value)
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second_value = WORD_NUMBERS.get(second.lower())
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if second_value is None:
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return None
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if first_value < 20 or first_value >= 100 or not 0 < second_value < 10:
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return None
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return float(first_value + second_value)
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def _claimed(pos: int, spans: list[tuple[int, int]]) -> bool:
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"""Whether a numeric token at ``pos`` was already claimed by an earlier pass."""
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return any(start <= pos < end for start, end in spans)
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def extract_quantities(problem_text: str) -> tuple[Quantity, ...]:
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"""Extract ``(value, unit, source_token)`` quantities in left-to-right order.
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Deterministic. ``source_token`` is the surface number string (used by the
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self-verification gate to prove the value is grounded in the text). Units are
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lowercased; the value's surface token is preserved verbatim.
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Passes run most-specific first and claim the digit spans they consume so later
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passes never double-count a number:
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1. EX-4 same-unit list (claims every number in the list);
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2. digit + single unit word (skips numbers a list already claimed);
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3. EX-1 word-number + unit word (alphabetic, disjoint from digit spans);
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4. EX-5 sentence-final bare number (skips any already-claimed digit).
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"""
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found: list[tuple[int, Quantity]] = []
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claimed: list[tuple[int, int]] = []
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# 1. EX-4 — list with one trailing unit; the unit inherits to every number.
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for match in _LIST_WITH_TRAILING_UNIT_RE.finditer(problem_text):
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unit = match.group(2).lower()
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for num in _NUMBER_RE.finditer(match.group(1)):
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pos = match.start(1) + num.start()
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quantity = _quantity(num.group(0), unit)
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if quantity is not None:
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found.append((pos, quantity))
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claimed.append((pos, pos + len(num.group(0))))
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# 2. digit + single unit word — the original base pattern.
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for match in _QTY_RE.finditer(problem_text):
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if _claimed(match.start(1), claimed):
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continue
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quantity = _quantity(match.group(1), match.group(2))
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if quantity is not None:
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found.append((match.start(1), quantity))
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claimed.append(match.span(1))
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# 3. EX-1 — word-numbers (and tens-one hyphen compounds) with a unit word.
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for match in _WORD_QTY_RE.finditer(problem_text):
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value = _resolve_word_number(match.group(1), match.group(2))
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if value is None:
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continue
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source_token = (
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match.group(1)
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if match.group(2) is None
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else match.group(0).rsplit(maxsplit=1)[0]
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)
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found.append(
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(
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match.start(1),
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Quantity(value=value, unit=_clean_unit(match.group(3)), source_token=source_token),
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)
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)
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# 4. EX-5 — sentence-final bare numbers (empty unit).
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for match in _FINAL_NUMBER_RE.finditer(problem_text):
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if _claimed(match.start(1), claimed):
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continue
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quantity = _quantity(match.group(1), "")
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if quantity is not None:
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found.append((match.start(1), quantity))
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found.sort(key=lambda item: item[0])
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return tuple(quantity for _, quantity in found)
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