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Author SHA1 Message Date
Shay
e705f27d2e
docs(ADR-0164,0165): incremental comprehension reader + regex scope rule (#317)
Replace the regex sentence-template front-end of the math admissibility
layer with an incremental compositional reader. Lock the architectural
boundary that regex is permitted only at the lexeme level, never as
sentence-structure templates.

ADR-0164 (Proposed) — Incremental Comprehension Reader. Word-by-word
state accumulation over a closed set of semantic categories, with the
operational lexicon living as a pack-shaped data artifact under
language_packs/data/en_core_math_v1/. Reader output type matches the
existing regex parser's output, so the binding-graph admissibility
(ADR-0132/0133/0134/0135), the solver (ADR-0116), and the verifier
(ADR-0117) stay unchanged. wrong=0 is preserved by construction —
the reader produces inputs to the existing admissibility gate, not a
bypass around it. Phased coexistence with the regex layer during
transition; regex sentence templates removed in Phase 3.

ADR-0165 (Proposed) — Regex Scope Rule. Structural invariant: regex
matches one piece of orthographic material with a closed rule
(currency literal, fraction literal, percentage, time-amount, closed
unit-noun sets), never a sentence shape. Lexeme-primitive registry is
closed and grown through the same contemplation -> proposal -> HITL
review corridor that grows vocabulary (ADR-0150 / 0152 / 0155 / 0161).
The engine acquires new recognition tools through reviewed teaching,
not through operator edits to parser code.

ADR-0163's diagnosis (front-end is the bottleneck) is reaffirmed.
Its Phase B-E prescription (regex DerivedRecognizers via
recognizer_match.py) is partially superseded by ADR-0164. ADR-0136
and its S-family (S.1 / S.2 / S.3 / S.4) have the same disposition:
regex sentence-template prescription superseded; empirical refusal
taxonomies and closed-set vocabulary preserved as lexicon seed.
The HITL corridor architecture is preserved; what flows through it
changes from regex recognizers to lexicon entries, categories, and
lexeme primitives.

Session log SESSION-2026-05-26-comprehension-reader.md captures the
narrative of how this decision emerged from the post-D.2 train-sample
baseline review (correct=3 refused=47 wrong=0, 34/47 refusals at the
question gate).

No runtime code changes. ADRs only.
2026-05-26 19:23:05 -07:00
Shay
e7a1ffb72e
feat(ADR-0136.S.2): conditional-op question — gsm8k-0042 admits, wrong==0 (#203)
Adds CandidateConditionalOpQuestion + extractor for the closed shape:
  "If <Entity> <verb> <N> <unit>, how many <unit2> does <Entity2> <aux> [<qualifier>]?"

In parse_and_solve, when the question yields exactly one such candidate
and exactly one matching InitialPossession exists by (entity, unit) across
all statement sentences, computes initial_value ± operand (verb polarity)
and emits when answer >= 0; refuses otherwise. Structurally identical to
S.1 capacity/earnings short-circuits.

GSM8K probe: 2/50 → 3/50 (+0042, answer=30.0), wrong stays 0.

- generate/math_candidate_parser.py: _COND_SUBTRACT_VERBS / _COND_ADD_VERBS
  closed sets; _COND_OP_Q_RE; extract_conditional_op_question_candidates
- generate/math_candidate_graph.py: short-circuit after earnings path
- tests/test_adr_0136_S2_conditional_op.py: 25 tests (extractor unit tests,
  end-to-end short-circuit, B3 + S.1 regression guards, post-S.2 honest
  admission count)
- docs/decisions/ADR-0136.S.2-conditional-op-question.md
2026-05-23 21:20:52 -07:00