7f67cea400
Closes the vocabulary gap: `combined` and `together` added to `_Q_TOTAL_RE` and `_Q_ENTITY_RE` tail alternations. Both map to `entity=None` semantics; the solver's existing sum path is unchanged. Ships: - Parser one-line regex extension (`generate/math_candidate_parser.py`) - 20-case curated axis lane (`G5_aggregate/v1/`) — 5 shapes × 4 cues - Runner + byte-equal report (20/20 pass, wrong=0) - 25 tests covering cue vocab, 2/3-entity sums, degenerate aggregate, refusals, byte-equality, B3 regression guard, GSM8K safety rail - ADR-0131.G.5 No admission movement on GSM8K probe (statement-parse bottleneck unchanged).
89 lines
3.4 KiB
Markdown
89 lines
3.4 KiB
Markdown
# ADR-0131.G.5 — Aggregate Answer Composition
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**Status:** Accepted
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**Parent:** [ADR-0131.G — GSM8K Coverage Probe](ADR-0131.G-gsm8k-coverage-probe.md)
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**Date:** 2026-05-23
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## Context
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The aggregate-answer path — questions like "How many apples do they have
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altogether?" — was functionally complete before this ADR. The parser
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(`_Q_TOTAL_RE` in `generate/math_candidate_parser.py`) already emitted
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`Unknown(entity=None, unit=<unit>)` for aggregate cues, and the solver
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(`generate/math_solver.py`) already summed all terminal state entries
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matching the questioned unit when `entity is None`.
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What was missing:
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1. **Vocabulary gap (now closed):** `"combined"` and `"together"` were
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absent from `_Q_TOTAL_RE`'s tail alternation, causing questions using
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those cues to be refused even when the solver would have produced the
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correct sum.
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2. **No pinned lane:** no curated axis cases proved the 2-entity,
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3-entity, and degenerate aggregate paths end-to-end through
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`parse_and_solve`.
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## Decision
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### Closed aggregate-cue vocabulary
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Exactly four cues are admitted:
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| Cue | Example tail |
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|-----|-------------|
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| `in total` | "How many apples do they have in total?" |
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| `altogether` | "How many apples do they have altogether?" |
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| `combined` | "How many apples do they have combined?" |
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| `together` | "How many apples do they have together?" |
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All four map to `entity=None` semantics — the solver sums all state
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entries whose unit matches the questioned unit, across all entities.
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### Solver path (pre-existing)
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The `entity is None` branch in `_resolve_unknown` was not changed. It
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sums `v for (_, unit), v in state.items() if unit == unknown.unit`.
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This ADR extends the cue vocabulary and pins the lane, not the solver.
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### Axis lane
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20 curated cases at `evals/math_capability_axes/G5_aggregate/v1/cases.jsonl`:
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| Shape | Count | Purpose |
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|-------|-------|---------|
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| 2-entity sum, no operations | 4 | one case per cue |
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| 3-entity sum, no operations | 4 | one case per cue |
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| 2-entity sum with add/subtract op | 4 | mixed cues |
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| Single-entity degenerate | 4 | regression guard |
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| Refusal: outside closed cue | 4 | wrong==0 probe |
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Refusal cases use question forms outside the closed `_Q_TOTAL_RE`
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pattern (e.g., "How many apples does everyone have?", "What is the
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total number of coins?") to verify the parser correctly refuses
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paraphrases not in the closed cue set.
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### Gate
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`wrong == 0` on every axis case. GSM8K `admitted_wrong == 0` preserved
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(no admission movement expected — all 50 sample cases still refuse at
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statement parsing; question-layer work cannot lift that).
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## Deferred
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- **Implicit aggregation without a cue word:** "How many apples do Sam
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and Tom have?" requires coreference resolution (named-entity →
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pronoun-equivalent grouping). Out of scope for the closed-cue model.
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- **Rate-based aggregation:** "How many dollars did they earn in total?"
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where the unit derives from a rate operation. Requires rate-verb
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support in the statement parser.
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- **GSM8K admission lift:** all 50 sample cases fail at statement
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parsing (rate verbs, compound sentences, implicit entities).
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Question-layer cue extensions cannot move that number.
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## Evidence
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- Axis runner: `evals/math_capability_axes/G5_aggregate/v1/runner.py`
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- Report: `evals/math_capability_axes/G5_aggregate/v1/report.json`
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- Tests: `tests/test_adr_0131_G5_aggregate.py`
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- B3 lane unchanged.
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- GSM8K `admitted_wrong == 0` preserved.
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