core/docs/adr/ADR-0136.S.1-rate-event-statements.md
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ADR-0136.S.1 — Rate/Event Statement Parsing

Status: Accepted — regex patterns scheduled for removal under ADR-0164 Phase 3; closed-set vocabulary preserved as lexicon seed Parent: ADR-0136 (Statement Layer Corridor) — see ADR-0136 §Amendment 2026-05-26 Date: 2026-05-23

Context

The GSM8K refusal taxonomy (evals/gsm8k_math/train_sample/v1/refusal_taxonomy.json) reveals that 23/50 cases are blocked by context-filler sentences (correctly refused — no parseable numeric state), while 4/50 have rate/capacity/price as their primary barrier. The remaining cases are compound-statement, distributive-multiply, and diverse long-tail shapes.

This ADR targets the 4 rate-class cases with two closed statement shapes.

Taxonomy Finding

Primary barrier Cases S.1 scope?
context_filler 23 No — correctly refused
rate/capacity/price 4 Yes
compound_statement 5 No
distributive_multiply 1 (+5 secondary) No
diverse long-tail 17 No

Closed Verb Sets

Capacity verbs: shuck, pick, pack, make, produce, type, read, write, paint, run, score, answer, complete (+ third-person -s forms).

Earnings verbs: make, earn, receive, get, charge (+ third-person -s forms).

No regex wildcards for verbs — every admitted verb is explicitly listed in a frozen set. Sentences with verbs outside the closed set are refused (not wrong).

Short-Circuit Rationale

Both rate shapes bypass the Cartesian-product candidate graph because the rate computation is a direct rate × time multiplication with unit conversion, not a graph of initial-possessions and operations. The short-circuit runs before _filtered_statement_choices so that rate-shaped sentences don't trigger the "no admissible candidate" refusal.

Actor matching is required: capacity questions with pronouns (he/she) accept any actor; named-actor questions require case-insensitive match. Mismatched actors produce refusal, not wrong answers.

Honest GSM8K Claim

  • Pre-S.1: 0/50 admitted (all refused).
  • Post-S.1: 1/50 admitted — gsm8k-0014 (Bob shucks oysters) with answer 240.0 (correct).
  • admitted_wrong = 0 (safety rail preserved).

The other 3 rate-class cases remain blocked by context-filler sentences in their opening statements; the rate parsing behind them is irrelevant until those sentences parse.

Deferred

  • Context-filler gated problems (23 cases — needs semantic classification of narrative scene-setter sentences).
  • Conditional branching (overtime rules, e.g. "if she works more than 8 hours").
  • Percentage/interest rates (10% simple interest).
  • Multi-statement earnings (duration asserted in a separate sentence from the rate — needs general duration-statement parser).

Evidence

  • Axis lane: evals/math_capability_axes/S1_rate_events/v1/ — 20/20 pass, wrong=0.
  • B3 bounded-grammar lane: unchanged (wrong=0).
  • GSM8K candidate-graph probe: wrong=0, admitted=1/50.
  • Tests: tests/test_adr_0136_S1_rate_events.py — ≥15 tests including B3 regression guard and GSM8K admitted_wrong=0 rail.