# ADR-0136.S.1 — Rate/Event Statement Parsing

**Status:** Accepted — *regex patterns scheduled for removal under [ADR-0164](./ADR-0164-incremental-comprehension-reader.md) Phase 3; closed-set vocabulary preserved as lexicon seed*
**Parent:** ADR-0136 (Statement Layer Corridor) — see [ADR-0136 §Amendment 2026-05-26](./ADR-0136-statement-layer-corridor.md)
**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.
