Merge pull request #165 from AssetOverflow/feat/adr-0127-0128-pack-integration
feat(ADR-0127/0128 integration): pack-aware parser + Path-B trigger result
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docs/decisions/ADR-0127-0128-RESULTS.md
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docs/decisions/ADR-0127-0128-RESULTS.md
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# ADR-0127 + ADR-0128 Results — Path-B Triggered
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**Status:** Empirical result; load-bearing for the GSM8K-math arc decision
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**Date:** 2026-05-23
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**Author:** CORE agents + reviewers
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**Depends on:** ADR-0126 (architecture), ADR-0127 (units pack),
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ADR-0128 (numerics pack), ADR-0114a (10 anti-overfitting obligations),
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ADR-0119 (+ all 8 sub-phases), ADR-0120 (expert promotion contract),
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ADR-0121 (math expert promotion deferred)
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---
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## TL;DR
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The ADR-0126 → 0127 → 0128 arc shipped the full deterministic
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design that the parser-by-rule + units-substrate hypothesis
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required. The empirical result on the GSM8K train sample is:
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```
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correct = 0 / 50
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wrong = 0 / 50 (wrong == 0 preserved)
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refused = 50 / 50
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```
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Per ADR-0127's exit criterion and the Path-A vs Path-B decision
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documented in ADR-0126: **the deterministic parser-by-rule
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architecture, with full units + numerics substrate, does not move
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the GSM8K-math lane.** This is the **real Path-B trigger.** The
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math expert promotion path retargets to a benchmark where exact
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recall and determinism are the discriminators — see
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"Recommendation" below.
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---
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## What was shipped
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| Layer | Module / Pack | What |
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|-------|---------------|------|
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| Architecture | `generate/math_roundtrip.py` | Round-trip admissibility primitive (26 tests, ADR-0126 P1) |
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| Architecture | `generate/math_candidate_parser.py` | Candidate-emitting sentence parser (17 tests, ADR-0126 P2) |
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| Architecture | `generate/math_candidate_graph.py` | Branch enumeration + decision rule (22 tests, ADR-0126 P3) |
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| Architecture | `evals/gsm8k_math/runner.py::_score_one_candidate_graph` | Runner wiring (9 tests, ADR-0126 P4) |
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| Substrate | `language_packs/data/en_units_v1/` | 284 lemmas, 401 conversion edges, NIST/ISO provenance (Gemini, PR #164) |
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| Substrate | `language_packs/data/en_numerics_v1/` | 130 lemmas across cardinals/ordinals/fractions/multipliers/quantifiers/comparison-anchors/format-rules (Opus #2, PR #163) |
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| Loader | `language_packs/loader.py` re-exports | Single import path for both packs (ADR-0127/0128 deferred coordination) |
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| Integration | `generate/math_candidate_parser.py::_canonicalize_unit` | Pack-aware unit canonicalization — handles irregular plurals (feet, children, etc.) via pack lookup |
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| Integration | `generate/math_candidate_parser.py::extract_initial_candidates` | Widened to `<Entity> has N <unit> [of <substance>]` + `There are N <unit> [in <place>]` shapes |
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| Integration | `generate/math_candidate_parser.py::_is_indefinite_quantifier` | ADR-0128.4 quantifier-driven refusal (`some`, `many`, etc. → no candidate emitted; preserves wrong == 0) |
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| Integration | `generate/math_candidate_parser.py` op-pattern trailing prep | Added `of` / `for` / `with` to the discardable preposition tail (ADR-0127 substance qualifier) |
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| Integration | `generate/math_roundtrip.py::_value_grounds` | Pack-backed cardinal lookup (widens word-number coverage from hard-coded 0-12 to full numerics pack) |
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| Integration | `evals/gsm8k_math/train_sample/v1/runner.py` | Swapped `_score_one` → `_score_one_candidate_graph` |
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## What measurably works (synthetic verification)
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The candidate-graph architecture + pack substrate solves the
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*kinds* of problems it was designed to solve. Six tailored
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synthetic cases verify end-to-end:
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| Case | Result |
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|------|--------|
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| `Jan has 5 apples. Jan buys 3 apples. How many apples does Jan have?` | ✓ 8 |
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| `Sam has 10 feet of rope. Sam uses 3 feet of rope. How many feet does Sam have?` | ✓ 7 (non-count unit; substance qualifier) |
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| `There are 5 kids in camp. How many kids do they have?` | ✓ 5 (implicit-subject shape) |
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| `Sam has 10 dollars. Sam spends 3 dollars. How many dollars does Sam have?` | ✓ 7 (money) |
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| `Sam has 5 hours. Sam uses 2 hours. How many hours does Sam have?` | ✓ 3 (time-dimension unit) |
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| `Sam has 10 children. Sam loses 2 children. How many children does Sam have?` | ✓ 8 (irregular plural via pack) |
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**1050/1050** existing test regression suites green across math,
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ADR-0126, ADR-0127 pack ratification, ADR-0128 pack ratification,
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and runner. Zero regressions from the integration work.
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## What did not move (empirical reality)
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The 50-case GSM8K train sample stays at 0 correct / 0 wrong / 50
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refused. Inspection of refusal causes shows that real GSM8K
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problems carry compound linguistic structure that no pack adds
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on its own:
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| Refusal class (from baseline categorization) | Train sample share | Pack-addressable? |
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|---|---|---|
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| OTHER_SHAPE (subordinate clauses, multi-word entities, possessives, pronouns across statements) | 27 / 50 | **No** — these need parser grammar work, not packs |
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| NON_COUNT_UNIT (`feet`, `hours`, etc.) | 8 / 50 | **Partial** — pack helps single-statement, but problems still chain across multiple statements that other gaps refuse |
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| MONEY (`$N`) | 5 / 50 | **Partial** — same multi-statement compound issue |
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| RATE (`per`, `each`) | 5 / 50 | Partial |
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| INDEFINITE_QUANT (`some`, `few`) | 3 / 50 | Yes — pack refuses cleanly, but refusal isn't correct |
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| CONTAINER_OF | 1 / 50 | Partial |
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| THERE_ARE | 1 / 50 | Yes (now parses), but other statements in same problem still refuse |
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The structural problem: a 3-5-sentence GSM8K problem refuses if
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*any* sentence has no admissible candidate. P(problem passes) =
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P(sentence passes)^N. The pack work raised per-sentence parse
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rate measurably on simple shapes, but the *joint* pass rate
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stayed at zero because every real problem contains at least one
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sentence the parser still can't handle.
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## Why this is the Path-B trigger ADR-0126 named
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ADR-0126's exit criterion documented two outcomes:
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> **If passed:** if 50-case train sample shows correct ≥ 10/50
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> with wrong == 0, the architecture is validated; run the sealed
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> holdout.
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>
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> **If missed:** if 50-case train sample shows correct < 10/50,
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> the parser-by-rule architecture (in any topology) is the wrong
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> abstraction for GSM8K coverage. ADR-0126 itself is deferred and
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> the work pivots to benchmark re-selection.
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ADR-0127's exit criterion sharpened this: re-run train sample
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with units pack mounted; if still missed, the failure is *real*
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(architecture + substrate both insufficient).
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ADR-0128 added the numerics pack to the same exit criterion.
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All three packs are mounted, the architecture is in place, the
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substrate is exhaustive (284 unit lemmas + 130 numeric lemmas +
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401 conversion edges), and the result is 0/50.
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**This is the moment the architectural arc was designed to
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surface a decision.** The deterministic design is correct,
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load-bearing, and complete; it does not produce GSM8K coverage
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because GSM8K's linguistic distribution is not parseable by any
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deterministic rule set at the rate the substrate enables. The
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27/50 OTHER_SHAPE refusals are the empirical evidence that the
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gap is *grammar coverage of paraphrase variance*, not any
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specific missing pack lemma.
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## What `wrong == 0` actually bought us
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Despite 0/50 correct, the wrong-zero discipline produced a
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sound, replay-deterministic, audit-trail-complete pipeline that:
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- Refuses honestly on every case it cannot handle
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- Carries pack-grounded provenance on every emitted operation
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- Round-trip-verifies every parsed slot against source tokens
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- Passes every adversarial gate
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- Composes with the existing teaching subsystem's reviewed-
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correction discipline
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This is genuinely useful infrastructure. The verdict is "wrong
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benchmark for this architecture's strengths," not "the
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architecture is bad."
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## Recommendation: Path B
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Three sub-decisions:
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### 1. Demote GSM8K-math lane from the math expert promotion contract.
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GSM8K is retained as a stress test and as a "we honestly refuse
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on this distribution" demonstration, but **`correct_rate` on
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GSM8K is removed from the ADR-0120 expert-promotion gate** for
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the `mathematics_logic` domain.
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### 2. Re-target the math expert promotion to a benchmark where exact-recall + determinism are discriminators.
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Candidates:
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- **MATH symbolic subset** — symbolic-equivalence problems where
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exact algebraic recall is the right primitive
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- **CORE-native teaching-corpus eval** — problems sourced from
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ratified teaching chains, where the parser's grammar exactly
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matches the corpus's surface forms by construction (no
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paraphrase-variance gap)
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- **A curated word-problem set** with bounded grammar (e.g.,
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Khan Academy style problems pre-filtered to single-sentence
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arithmetic shapes)
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A separate ADR (proposed: ADR-0131) scopes the re-targeting
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decision and exit criteria.
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### 3. ADR-0126 / 0127 / 0128 substrate stays in main as load-bearing infrastructure.
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The candidate-graph topology, the round-trip admissibility
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primitive, the units pack, the numerics pack, and the
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deterministic pack-aware parser are useful for:
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- Any future deterministic word-problem benchmark
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- The teaching corpus's own evaluation lane (where grammar match
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is by-construction)
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- Future cross-language packs (`es_units_v1`, `es_numerics_v1`)
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that reuse the architecture
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- Operator interaction surfaces where deterministic refusal +
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honest provenance matter more than raw coverage
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**Do not revert.** This work proved a hypothesis correctly even
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though the hypothesis didn't pan out for GSM8K.
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## What this does NOT recommend
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- Does **not** recommend abandoning the deterministic engine
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philosophy. The architecture works; the benchmark choice was
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the error.
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- Does **not** recommend pulling in LLM-assisted parsing or
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any opaque component. The contract integrity is intact and
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worth preserving.
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- Does **not** recommend more parser regex expansion within the
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current architecture for GSM8K. Four previous ADRs in that
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shape produced 0 lift; this one (the architectural pivot) did
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the same. The treadmill has been independently characterized
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twice now.
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## Composition with deferred backlog (ADR-0129 / ADR-0130)
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The deferred teaching-loop ADRs (`spaced-correction-replay`,
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`pre-articulation-calibration`) become more interesting once Path
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B lands a new benchmark, because:
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- A benchmark where the parser handles by-construction grammar
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cleanly will produce a stable correction-store population —
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the precondition ADR-0129 named for un-deferral.
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- A new benchmark's per-version calibration cohorts give
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ADR-0130 a real signal to measure.
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These remain deferred under the new path, but their un-deferral
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exit criteria become reachable.
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## PR checklist
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```
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What capability did this add?
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→ The integration layer that wires en_units_v1 + en_numerics_v1
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into the ADR-0126 candidate-graph parser. Pack-aware unit
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canonicalization, indefinite-quantifier refusal, substance-
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qualifier handling, There-are initial shape, pack-backed
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cardinal grounding. Also the Path-B trigger evidence.
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What invariant proves the field remains valid?
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→ wrong == 0 preserved on train sample (0/50 wrong). Trace
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determinism preserved. Round-trip admissibility extended
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with pack-typed unit grounding.
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Which CLI suite/eval proves the lane?
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→ smoke + math + packs + train_sample_runner. All 1050 tests
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green; train sample re-runs deterministic 0/0/50.
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Did this avoid hidden normalization, stochastic fallback,
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approximate recall, unreviewed mutation?
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→ Yes. Pack lookups are deterministic. Indefinite quantifier
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refusal is a deliberate hard-no, not a probabilistic
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threshold. No LLM fallback added.
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If it touches user input, what trust boundary was enforced?
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→ No new user-input surfaces. Pack loaders already validate
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pack_id via safe_pack_id (ADR-0051). Train sample is
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unsealed by design (drawn from GSM8K train split, not
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holdout).
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```
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@ -18,7 +18,7 @@
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},
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{
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"case_id": "gsm8k-train-sample-v1-0002",
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"reason": "candidate_graph: no admissible candidate for statement: 'Jan buys 1000 feet of cable.'",
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"reason": "candidate_graph: no admissible candidate for statement: 'She splits it up into 25-foot sections.'",
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"verdict": "refused"
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},
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{
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@ -213,7 +213,7 @@
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},
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{
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"case_id": "gsm8k-train-sample-v1-0041",
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"reason": "candidate_graph: no admissible candidate for statement: 'Troy bakes 2 pans of brownies, cut into 16 pieces per pan.'",
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"reason": "candidate_graph: no admissible candidate for statement: 'The guests eat all of 1 pan, and 75% of the 2nd pan.'",
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"verdict": "refused"
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},
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{
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@ -75,9 +75,11 @@ class CandidateInitial:
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matched_entity_token: str
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def __post_init__(self) -> None:
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if self.matched_anchor.lower() not in ("has", "have"):
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# ADR-0127 widens the anchor set to include 'there are/were/is/was'
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# for the implicit-subject initial-possession shape.
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if self.matched_anchor.lower() not in ("has", "have", "are", "were", "is", "was"):
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raise ValueError(
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f"CandidateInitial.matched_anchor must be has/have; "
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f"CandidateInitial.matched_anchor must be has/have/are/were/is/was; "
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f"got {self.matched_anchor!r}"
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)
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@ -120,7 +122,28 @@ _INITIAL_HAS_RE: Final[re.Pattern[str]] = re.compile(
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rf"^(?P<entity>{_ENTITY})\s+"
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rf"(?P<anchor>has|have)\s+"
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rf"(?P<value>{_VALUE})\s+"
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r"(?P<unit>\w+)\s*\.?$"
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r"(?P<unit>\w+)"
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# ADR-0127 substance qualifier: "Sam has 5 feet of rope" — the
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# 'of <NP>' tail is grammatically real but arithmetically inert.
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r"(?:\s+of\s+.+)?"
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r"\s*\.?$"
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)
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# ADR-0127 "There are/were N <unit> [in <place>]" initial-possession shape.
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# The implicit-subject anchor 'there are' is the only initial-possession
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# shape that doesn't name an entity in the source; we treat the
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# place phrase (when present) as the entity and treat the unit as the
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# count noun. When no place is named, the entity is the unit itself
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# (collective). Indefinite quantifiers ('some', 'few', 'many') in the
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# value slot are refused upstream by extract_initial_candidates via
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# the quantifier-driven refusal helper (ADR-0128.4).
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_INITIAL_THERE_ARE_RE: Final[re.Pattern[str]] = re.compile(
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r"^There\s+(?P<anchor>are|were|is|was)\s+"
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rf"(?P<value>{_VALUE})\s+"
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r"(?P<unit>\w+)"
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r"(?:\s+in\s+(?P<place>[A-Za-z]\w*(?:\s+\w+)?))?"
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r"\s*\.?$",
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flags=re.IGNORECASE,
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)
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@ -139,36 +162,93 @@ def _resolve_value(value_token: str) -> int:
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return WORD_NUMBERS[value_token.lower()]
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def _is_indefinite_quantifier(token: str) -> bool:
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"""ADR-0128.4 — quantifier-driven refusal helper.
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Returns True when ``token`` resolves (via en_numerics_v1 lookup) to
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an indefinite quantifier (``some``, ``many``, ``few``, ``several``,
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etc.). Indefinite quantifiers in value-slot positions are refused
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rather than guessed — preserves wrong == 0.
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"""
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try:
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from language_packs.loader import lookup_quantifier
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entry = lookup_quantifier(token.lower())
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if entry is not None and entry.semantic_type == "indefinite":
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return True
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except Exception:
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pass
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return False
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def extract_initial_candidates(sentence: str) -> list[CandidateInitial]:
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"""Return all admissible initial-possession candidates for ``sentence``.
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Currently emits at most one candidate (the single canonical shape
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"<Entity> has <N> <unit>"). Returns an empty list if no shape matches.
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Recognized shapes:
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1. "<Entity> has <N> <unit> [of <substance>]" — canonical.
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2. "There are <N> <unit> [in <place>]" — implicit-subject shape.
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ADR-0128.4: if the value slot resolves to an indefinite quantifier
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(`some kids`, `many things`), no candidate is emitted (refusal
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preserves wrong == 0).
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"""
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s = sentence.strip().rstrip(".")
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out: list[CandidateInitial] = []
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m = _INITIAL_HAS_RE.match(s)
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if not m:
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return []
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entity = _normalize_entity(m.group("entity"))
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value = _resolve_value(m.group("value"))
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unit_raw = m.group("unit")
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# Canonicalize: lowercase + ensure plural (matching math_parser._canonical_unit).
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unit = unit_raw.lower()
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if not unit.endswith("s"):
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unit = unit + "s"
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return [
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CandidateInitial(
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initial=InitialPossession(
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entity=entity,
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quantity=Quantity(value=value, unit=unit),
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),
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source_span=sentence,
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matched_anchor=m.group("anchor"),
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matched_value_token=m.group("value"),
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matched_unit_token=unit_raw,
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matched_entity_token=m.group("entity"),
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)
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]
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if m is not None:
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value_raw = m.group("value")
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if not _is_indefinite_quantifier(value_raw):
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entity = _normalize_entity(m.group("entity"))
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value = _resolve_value(value_raw)
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unit_raw = m.group("unit")
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unit = _canonicalize_unit(unit_raw)
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out.append(
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CandidateInitial(
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initial=InitialPossession(
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entity=entity,
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quantity=Quantity(value=value, unit=unit),
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),
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source_span=sentence,
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matched_anchor=m.group("anchor"),
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matched_value_token=value_raw,
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matched_unit_token=unit_raw,
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matched_entity_token=m.group("entity"),
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)
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)
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m2 = _INITIAL_THERE_ARE_RE.match(s)
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if m2 is not None:
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value_raw = m2.group("value")
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if not _is_indefinite_quantifier(value_raw):
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unit_raw = m2.group("unit")
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unit = _canonicalize_unit(unit_raw)
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value = _resolve_value(value_raw)
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place = m2.group("place")
|
||||
# When a 'in <place>' phrase is present, treat the place as
|
||||
# the implicit entity. Otherwise use the unit's plural as
|
||||
# the collective entity name (deterministic, derivable from
|
||||
# the source: "There are 5 kids" -> entity='kids').
|
||||
if place is not None:
|
||||
entity = _normalize_entity(place)
|
||||
entity_token = place
|
||||
else:
|
||||
entity = unit
|
||||
entity_token = unit_raw
|
||||
out.append(
|
||||
CandidateInitial(
|
||||
initial=InitialPossession(
|
||||
entity=entity,
|
||||
quantity=Quantity(value=value, unit=unit),
|
||||
),
|
||||
source_span=sentence,
|
||||
matched_anchor=m2.group("anchor"),
|
||||
matched_value_token=value_raw,
|
||||
matched_unit_token=unit_raw,
|
||||
matched_entity_token=entity_token,
|
||||
)
|
||||
)
|
||||
|
||||
return out
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
|
|
@ -200,13 +280,16 @@ def _op_pattern(verbs_pattern: str, *, requires_target: bool) -> re.Pattern[str]
|
|||
if requires_target:
|
||||
target_part = r"\s+to\s+(?P<target>[A-Z]\w+)"
|
||||
trailing_prep = (
|
||||
r"(?:\s+(?:on|from|at|in|onto|into|under|over)\s+.+)?"
|
||||
r"(?:\s+(?:on|from|at|in|onto|into|under|over|of|for|with)\s+.+)?"
|
||||
)
|
||||
else:
|
||||
target_part = ""
|
||||
# Note: 'to' is included in the discardable preposition set.
|
||||
# 'to' is included in the discardable preposition set.
|
||||
# 'of' is included for ADR-0127 substance qualifiers ("1000 feet
|
||||
# of cable") — the substance NP is grammatically real but
|
||||
# arithmetically inert; the unit slot carries the dimensional info.
|
||||
trailing_prep = (
|
||||
r"(?:\s+(?:on|from|at|in|onto|into|under|over|to)\s+.+)?"
|
||||
r"(?:\s+(?:on|from|at|in|onto|into|under|over|to|of|for|with)\s+.+)?"
|
||||
)
|
||||
return re.compile(
|
||||
r"^"
|
||||
|
|
@ -228,6 +311,27 @@ _SUBTRACT_OP_RE: Final[re.Pattern[str]] = _op_pattern(_SUBTRACT_VERBS_PATTERN, r
|
|||
_TRANSFER_OP_RE: Final[re.Pattern[str]] = _op_pattern(_TRANSFER_VERBS_PATTERN, requires_target=True)
|
||||
|
||||
|
||||
def _canonicalize_unit(unit_raw: str) -> str:
|
||||
"""Canonicalize a unit surface token to its plural form.
|
||||
|
||||
ADR-0127 integration: consult en_units_v1 first. If the token is a
|
||||
pack-recognized unit, use the pack's canonical plural form (handles
|
||||
irregular plurals like feet/feet, children, mice, etc. correctly).
|
||||
Otherwise fall back to the legacy '+s' rule for count nouns.
|
||||
"""
|
||||
lowered = unit_raw.lower()
|
||||
try:
|
||||
from language_packs.loader import lookup_unit
|
||||
entry = lookup_unit(lowered)
|
||||
if entry is not None:
|
||||
return entry.plural.lower()
|
||||
except Exception:
|
||||
pass
|
||||
if not lowered.endswith("s"):
|
||||
return lowered + "s"
|
||||
return lowered
|
||||
|
||||
|
||||
def _build_op_candidate(
|
||||
m: re.Match[str], kind: str, source: str
|
||||
) -> CandidateOperation | None:
|
||||
|
|
@ -237,9 +341,7 @@ def _build_op_candidate(
|
|||
unit_raw = m.group("unit")
|
||||
if unit_raw is None:
|
||||
return None
|
||||
unit = unit_raw.lower()
|
||||
if not unit.endswith("s"):
|
||||
unit = unit + "s"
|
||||
unit = _canonicalize_unit(unit_raw)
|
||||
subject = _normalize_entity(m.group("subject"))
|
||||
verb = m.group("verb").lower()
|
||||
value = _resolve_value(m.group("value"))
|
||||
|
|
@ -324,9 +426,7 @@ def extract_question_candidates(sentence: str) -> list[CandidateUnknown]:
|
|||
m = _Q_TOTAL_RE.match(s)
|
||||
if m is not None:
|
||||
unit_raw = m.group("unit")
|
||||
unit = unit_raw.lower()
|
||||
if not unit.endswith("s"):
|
||||
unit = unit + "s"
|
||||
unit = _canonicalize_unit(unit_raw)
|
||||
out.append(
|
||||
CandidateUnknown(
|
||||
unknown=Unknown(entity=None, unit=unit),
|
||||
|
|
@ -340,9 +440,7 @@ def extract_question_candidates(sentence: str) -> list[CandidateUnknown]:
|
|||
m = _Q_ENTITY_RE.match(s)
|
||||
if m is not None:
|
||||
unit_raw = m.group("unit")
|
||||
unit = unit_raw.lower()
|
||||
if not unit.endswith("s"):
|
||||
unit = unit + "s"
|
||||
unit = _canonicalize_unit(unit_raw)
|
||||
entity = _normalize_entity(m.group("entity"))
|
||||
out.append(
|
||||
CandidateUnknown(
|
||||
|
|
|
|||
|
|
@ -275,16 +275,37 @@ def _token_in(needle: str, haystack_tokens: frozenset[str]) -> bool:
|
|||
def _value_grounds(value_token: str, haystack_tokens: frozenset[str]) -> bool:
|
||||
"""A numeric value grounds if its surface token appears, OR if the token
|
||||
is a digit-string and any equivalent word-form appears, OR if it's a
|
||||
word-form and the digit appears."""
|
||||
word-form and the digit appears.
|
||||
|
||||
ADR-0128 integration: en_numerics_v1's cardinal table is consulted in
|
||||
addition to the legacy hard-coded WORD_NUMBERS, widening coverage from
|
||||
1-12 to the full pack cardinal range (0-1000+ plus compound rule). The
|
||||
hard-coded WORD_NUMBERS remains as a fast path and as a fallback if
|
||||
the pack is unavailable; the pack adds, never replaces.
|
||||
"""
|
||||
if _token_in(value_token, haystack_tokens):
|
||||
return True
|
||||
# word -> digit equivalent
|
||||
lowered = value_token.lower()
|
||||
|
||||
# Pack-backed cardinal lookup (ADR-0128). Soft import — if the pack
|
||||
# isn't mounted (e.g., in legacy test environments) we silently fall
|
||||
# through to the hard-coded table.
|
||||
try:
|
||||
from language_packs.loader import lookup_cardinal
|
||||
entry = lookup_cardinal(lowered)
|
||||
if entry is not None:
|
||||
digit = str(entry.numeric_value)
|
||||
if digit in haystack_tokens:
|
||||
return True
|
||||
except Exception:
|
||||
pass # fall through to hard-coded path
|
||||
|
||||
# word -> digit equivalent (legacy)
|
||||
if lowered in WORD_NUMBERS:
|
||||
digit = str(WORD_NUMBERS[lowered])
|
||||
if digit in haystack_tokens:
|
||||
return True
|
||||
# digit -> any word with that integer value
|
||||
# digit -> any word with that integer value (legacy)
|
||||
try:
|
||||
n = int(value_token)
|
||||
except ValueError:
|
||||
|
|
@ -292,6 +313,15 @@ def _value_grounds(value_token: str, haystack_tokens: frozenset[str]) -> bool:
|
|||
for word, w_val in WORD_NUMBERS.items():
|
||||
if w_val == n and word in haystack_tokens:
|
||||
return True
|
||||
# Pack-backed reverse lookup: digit -> cardinal surface in haystack
|
||||
try:
|
||||
from language_packs.loader import lookup_cardinal
|
||||
for tok in haystack_tokens:
|
||||
entry = lookup_cardinal(tok)
|
||||
if entry is not None and entry.numeric_value == n:
|
||||
return True
|
||||
except Exception:
|
||||
pass
|
||||
return False
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -288,3 +288,68 @@ def canonical_unit_for(dimension: str) -> str:
|
|||
if unit:
|
||||
return unit.singular
|
||||
return dim.canonical_unit
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# ADR-0128 numerics-pack re-exports (deferred coordination from ADR-0128 brief)
|
||||
#
|
||||
# en_numerics_v1's loader functions live in language_packs/numerics_loader.py
|
||||
# (per the brief's concurrency clause that allowed parallel development).
|
||||
# Re-exporting them here gives callers a single import path
|
||||
# (`from language_packs.loader import lookup_cardinal`) while keeping the
|
||||
# numerics implementation in its own domain-cohesive module.
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
from language_packs.numerics_loader import ( # noqa: E402
|
||||
CardinalEntry,
|
||||
ComparisonAnchorEntry,
|
||||
FractionEntry,
|
||||
MultiplierEntry,
|
||||
NumberFormatEntry,
|
||||
OrdinalEntry,
|
||||
ParsedNumber,
|
||||
QuantifierEntry,
|
||||
lookup_cardinal,
|
||||
lookup_comparison_anchor,
|
||||
lookup_comparison_anchors,
|
||||
lookup_fraction,
|
||||
lookup_multiplier,
|
||||
lookup_ordinal,
|
||||
lookup_quantifier,
|
||||
match_number_format,
|
||||
number_format_entries,
|
||||
parse_compound_cardinal,
|
||||
)
|
||||
|
||||
__all__ = [
|
||||
# ADR-0127 units pack
|
||||
"UnitEntry",
|
||||
"ContainerEntry",
|
||||
"DimensionEntry",
|
||||
"ConversionEdge",
|
||||
"ConversionGraph",
|
||||
"lookup_unit",
|
||||
"lookup_container",
|
||||
"lookup_dimension",
|
||||
"get_conversion_graph",
|
||||
"canonical_unit_for",
|
||||
# ADR-0128 numerics pack (re-exported from numerics_loader)
|
||||
"CardinalEntry",
|
||||
"OrdinalEntry",
|
||||
"FractionEntry",
|
||||
"MultiplierEntry",
|
||||
"QuantifierEntry",
|
||||
"ComparisonAnchorEntry",
|
||||
"NumberFormatEntry",
|
||||
"ParsedNumber",
|
||||
"lookup_cardinal",
|
||||
"lookup_ordinal",
|
||||
"lookup_fraction",
|
||||
"lookup_quantifier",
|
||||
"lookup_multiplier",
|
||||
"lookup_comparison_anchor",
|
||||
"lookup_comparison_anchors",
|
||||
"number_format_entries",
|
||||
"match_number_format",
|
||||
"parse_compound_cardinal",
|
||||
]
|
||||
|
|
|
|||
Loading…
Reference in a new issue