feat(derivation): Workstream A inc 3 — narrow rate connector follow-up (#799)
* docs(analysis): ratify Inc3 rate followup + v2 roadmap update (docs-first, pre any rate logic) * feat(derivation): Workstream A inc 3 — support 'one' connector in rate_with_currency injector (post docs ratification) * chore(derivation): clean Inc3 diff hygiene * chore(derivation): remove Inc3 formatting churn
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# CORE Problem-Solving Capability Roadmap v2 — 2026-06-17
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**Status:** Living document (docs-only update)
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**Date:** 2026-06-17
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**Context:** Post PR #797 (rate injection) + #798; preparing Inc3 rate follow-up before Gate A1 comparative injection.
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## Overview
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This v2 roadmap refines the GSM8K Workstream A path and the broader capability sequencing after the rate injection delivered by PR #797.
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As of 2026-06-17, PR #797 is merged and #798 is merged.
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## GSM8K Workstream A
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- Inc 1: reader/recognizer baseline lift (discrete etc.)
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- Inc 2: frontier measurement + stale doctrine repair + narrow rate injection (PR #797)
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- **Inc 3 (current seam):** Complete the post-#797 rate-follow-up evidence loop: run frontier report from current main, identify the remaining rate-family blocker, and ship at most one narrow Inc3 increment before comparative injection.
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### Recommended Inc3 target (narrow)
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Make the rate frontier evidence actionable by resolving the next narrow blocker exposed by #797.
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Scope candidates (in preference order for this increment):
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1. Denominator-state support for rate application (if failures surface as "actor has rate but no denom-unit quantity reachable").
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2. Safe connector expansion only if frontier proves "for one cup" is a dominant blocker.
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3. Measurement-only frontier report refresh if artifacts stale.
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Inc3 selected #2 (connector for "for one cup"/"one" token) because live debug on the pinned report + cases showed the exact remaining rate injector deferral from Inc2 (matcher left rate_anchor_token=None for "one"; spec unresolved_notes explicitly called it out for the Alexa surface). This was the minimal change that reclassifies the rate_with_currency no-injection bucket (making evidence actionable) while preserving all guards. Denom production is larger future work (see ratification for rationale and out-of-scope).
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"Complete and harden PR #797" is revised as: Complete the post-#797 rate-follow-up evidence loop: run frontier report from current main, identify the remaining rate-family blocker, and ship at most one narrow Inc3 increment before comparative injection.
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As of 2026-06-17, PR #797 is merged and #798 is merged.
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Explicitly: do not broaden to full rate language family, comparative injection, or non-rate categories in this increment.
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## Gate A1 / Comparative Injection
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Deferred until after the post-#797 rate follow-up loop is closed with Inc3 measurement.
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## Success Criteria for This Phase
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- Frontier report run on current main (train-sample proxy).
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- One narrow ratified Inc3 change.
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- Wrong=0 preserved on train_sample, practice, and relevant confusers.
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- Rate-family "recognized_no_injection" bucket reduced or its refusal mode made actionable (e.g. surfaces the true next blocker like denom reachability).
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- No rebaseline of sealed lanes or SHA movement without separate ratification.
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- Documentation (this roadmap + Inc3 ratification) committed as docs-first.
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## Out of Scope (for Inc3)
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- Full comparative (Gate A1) implementation.
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- Broad recognizer anchor work or other shape categories.
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- Changes to serving sealed paths.
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- Any mutation of identity, policy, or algebra invariants.
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Follow the ratified Inc3 doc for the exact bounded change.
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# GSM8K Workstream A Increment 3 — rate followup (post-#797) ratification
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**Date:** 2026-06-17
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**Workstream:** A
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**Increment:** 3 — post-#797 rate frontier evidence loop closure (narrow)
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**Status:** Ratified for implementation (BEFORE code changes)
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**Scope lock:** Bounded to making the rate "recognized_no_injection" bucket produce actionable evidence by resolving the explicit remaining connector blocker left open in #797. One smallest change only.
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## 1. Which exact refusal bucket is being attacked?
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From frontier report run on the (stale but authoritative post-#797) committed proxy `evals/gsm8k_math/train_sample/v1/report.json`:
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- Overall: 6 correct / 44 refused / 0 wrong (passed=false)
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- recognized_no_injection: 32
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- recognized_no_injection_by_category (rate relevant): rate_with_currency: 3
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The three rate_with_currency cases still emitting the "recognizer matched but produced no injection" (category=rate_with_currency) are exactly the ones referencing the surfaces left partially unhandled after Inc2:
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- 'Tina makes $18.00 an hour.' (category=rate_with_currency)
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- 'Alexa has a lemonade stand where she sells lemonade for $2 for one cup.' (category=rate_with_currency)
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- 'Erica lives near a lake where most locals sell fish as their main source of income, earning $20 per kg of fish.' (category=rate_with_currency)
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Post-#797, the matcher fires for all three and "an"/"per" surfaces now reach the injector and emit a CandidateOperation (verified by live debug on current main). The "for one cup" explicitly sets `rate_anchor_token: None` (see matcher comment and spec unresolved_notes: "Non-canonical 'for one X' framing").
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The injector returns () for the "one" case (and any elimination downstream for the others surfaces as the same top-level refusal reason because the statement-level inject did not contribute an admitted choice).
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This is the narrow remaining rate-family blocker visible in the rate bucket of the frontier analyzer.
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## 2. Which cases are expected to lift?
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- On the train_sample proxy: expected 0 net lift in correct count (the Alexa "for one cup" case uses inverse semantics — target cups from known revenue, not forward apply_rate on a held cup count; Tina/Erica denom qty statements use verbs/shapes that do not yet emit the required Initial for "hour"/"kg" unit). The change makes injection succeed for the "one" framing; the case will surface a downstream refusal reason ("no branch produced a solvable graph", "no admissible...", or "requires ... state") instead of the "no injection" one.
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- The rate_with_currency slice of recognized_no_injection is expected to drop from 3 (at least the connector case will no longer refuse at the injector boundary).
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- No change to non-rate buckets. Wrong remains 0.
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The primary deliverable is **actionable evidence**: after the change the frontier report will show the rate category either empty or reclassified to the true next blocker (denom state reachability), closing the post-#797 measurement loop without claiming a correct-count jump.
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## 3. Which confusers must still refuse?
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All existing confusers from the Inc2 ratification and test suite:
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- No denom state for the actor (e.g. isolated rate sentence).
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- Wrong actor (rate stated for A, quantity held by B).
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- Multiple rates in one sentence.
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- Time-unit without conversion (days vs hours).
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- Any surface that would produce ambiguous or ungrounded Rate / actor / verb.
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The change adds "one" only in the exact "for <one> <unit>" rate framing already present in the ratified rate_with_currency exemplars; no broadening of actor binding, no pronoun support, no new verbs outside the rate anchor list.
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## 4. What is the wrong=0 guard?
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- All paths still go through the existing five-layer net (matcher narrowness, source grounding in anchors, injector returns () on any construction failure, roundtrip_admissible + constraint propagation elimination, candidate-graph multi-branch disagreement + completeness).
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- New surfaces exercise the same `CandidateOperation` + `roundtrip_admissible` + `KIND_TO_VERBS["apply_rate"]` checks.
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- "one" treated as a surface alias only for the already-ratified "for one X" exemplar in the rate proposal; added to RATE_ANCHORS and injector allow-list with no other semantic change.
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- No sealed path touched (train_sample runner + serving use sealed=False).
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- Pre/post change: run the frontier script + `parse_and_solve` on the three rate surfaces + full proxy cases; assert wrong==0 on all.
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- The `tests/test_math_candidate_graph_rate_injection.py` and `test_gsm8k_frontier_report.py` continue to pass (the existing test already tolerates non-"no injection" refusals for the Alexa stmt).
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- If after change any train_sample case flips from refused to wrong, revert.
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## 5. Does this touch serving, sealed lanes, report.json, or solver semantics?
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- No changes to sealed injector lane (`_SEALED_INJECTORS` remains empty for this).
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- No write of updated report.json in this increment (proxy remains at 6/44/0 unless a later runner run is separately committed; the ratification does not require rebaseline).
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- No solver changes (`_apply_rate` unchanged; still requires denom state).
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- No graph construction or cartesian changes.
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- Touches only: the rate anchor token allow-list (matcher + roundtrip set + injector guard) + comments. This is the minimal patch to retire the explicit "narrow for Inc 2" deferral.
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- The frontier report script, ratification, and roadmap update are docs/evidence only.
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## 6. What is explicitly out of scope?
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- Denominator-state production (seeding Initials for "hour", "kg", "cup" from "works N hours", "trawled 80 kg", etc.). That is future work once the connector surface is closed and the frontier reclassifies the bucket.
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- Any change that would allow apply_rate without prior denom state.
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- "for one cup" solving (would require inverse/division op or goal-residual style for price-per).
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- Expansion to other temporal_aggregation, currency_amount, or non-rate categories.
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- Comparative injection / Gate A1.
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- Any movement of sealed SHAs, practice lane, or CLAIMS.
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- Broad verb or subject binding relaxations.
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- Re-running the train_sample runner and committing a new report.json as part of this PR (measurement-only refresh is out; the script run on the committed report is the evidence).
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## Implementation Notes (for the PR)
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- Smallest diff: 3 locations (RATE_ANCHORS, matcher "one" case, injector allow-list) + doc updates.
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- Update comments that say "narrow for Inc 2" or "deferred".
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- Run `uv run python scripts/gsm8k_frontier_report.py evals/gsm8k_math/train_sample/v1/report.json` before/after for the artifact.
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- `core test --suite gsm8k` or equivalent lane (pytest on the rate graph test + frontier test) + full `core test --suite full -q` before merge when practical.
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- Preserve `passed=false` on the proxy.
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This Inc3 closes the rate follow-up loop narrowly so that Ladder A has a clean evidence boundary before any comparative work.
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@ -150,7 +150,7 @@ COMPARE_MULTIPLICATIVE_ANCHORS: Final[frozenset[str]] = frozenset({
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# succeeds. "a"/"an" were documented in the comment but missing from the
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# set; added here (Inc 2) with corresponding injector tests.
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RATE_ANCHORS: Final[frozenset[str]] = frozenset({
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"per", "each", "every", "a", "an",
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"per", "each", "every", "a", "an", "one",
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})
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@ -591,7 +591,7 @@ def _locate_rate_verb(sentence: str) -> str | None:
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apply_rate. The literal form is required so CandidateOperation
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post-init + roundtrip_admissible grounding checks pass.
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"""
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rate_verbs = ("per", "each", "every", "a", "an")
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rate_verbs = ("per", "each", "every", "a", "an", "one")
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for raw in sentence.split():
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tok = raw.strip(".,;:!?\"'()[]{}").lower()
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if tok in rate_verbs:
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@ -670,11 +670,12 @@ def inject_rate_with_currency(
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# No whole-sentence fallback is allowed, because _locate_rate_verb
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# can still pick an unrelated earlier "a".
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rate_anchor_token = anchor.get("rate_anchor_token")
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if not rate_anchor_token or rate_anchor_token not in ("per", "each", "every", "a", "an"):
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# Missing or invalid connector for this rate surface (e.g. "one"
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# from "for one cup", or absent token). Refuse — do not emit
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# a CandidateOperation with a verb that does not belong to the
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# matched rate expression.
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if not rate_anchor_token or rate_anchor_token not in (
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"per", "each", "every", "a", "an", "one",
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):
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# Missing or invalid connector for this rate surface (e.g. absent
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# token). "one" (from "for one cup") is now supported (Inc 3).
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# Refuse on anything else.
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return ()
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verb_token = rate_anchor_token
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@ -340,11 +340,9 @@ def _match_rate_with_currency(
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elif m.group(8):
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q = m.group(8).lower()
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per_unit = m.group(9)
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if q in ("each", "every", "a"):
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if q in ("each", "every", "a", "one"):
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connector = q
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else:
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# "one" in "for one X" is not a direct RATE_ANCHORS token;
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# leave None so injector will refuse (narrow for Inc 2).
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connector = None
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if not per_unit:
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@ -29,8 +29,12 @@ from tests._phase_d_fixture import build_synthetic_registry
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_REPO_ROOT = Path(__file__).resolve().parent.parent
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_GSM8K_CASES = _REPO_ROOT / "evals" / "gsm8k_math" / "train_sample" / "v1" / "cases.jsonl"
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_GSM8K_REPORT = _REPO_ROOT / "evals" / "gsm8k_math" / "train_sample" / "v1" / "report.json"
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_GSM8K_CASES = (
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_REPO_ROOT / "evals" / "gsm8k_math" / "train_sample" / "v1" / "cases.jsonl"
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)
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_GSM8K_REPORT = (
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_REPO_ROOT / "evals" / "gsm8k_math" / "train_sample" / "v1" / "report.json"
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)
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@pytest.fixture(scope="module")
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@ -46,7 +50,9 @@ def with_synthetic_registry(
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"""Patch ``math_candidate_graph._load_ratified_registry_or_empty`` to
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return the synthetic registry for the duration of the test."""
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monkeypatch.setattr(
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cg, "_load_ratified_registry_or_empty", lambda: synthetic_registry,
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cg,
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"_load_ratified_registry_or_empty",
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lambda: synthetic_registry,
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)
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return synthetic_registry
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@ -89,31 +95,38 @@ def test_empty_registry_preserves_existing_refusal_reason() -> None:
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def test_recognized_rate_statement_refuses_explicitly_post_wrong_zero_fix(
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with_synthetic_registry: tuple[RatifiedRecognizer, ...],
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) -> None:
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"""With the rate_with_currency recognizer loaded, "Tina makes $18.00
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an hour" is recognized but the v1 injector returns () (the
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SentenceChoice union does not yet model rates — see ADR follow-up).
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"""With the rate_with_currency recognizer loaded (synthetic), rate surfaces
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that now have v1 injector support ("an" from Inc2, "one" from Inc3) are
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injected (CandidateOperation). The early "recognizer matched but produced
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no injection" refusal no longer triggers for these supported surfaces.
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Pre-#359 behavior: silently drop the recognized-but-uninjectable
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statement and admit a partial graph from the rest — a wrong>0
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hazard analogous to case 0050.
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The full sentence provides no denom-unit Initial for the actor, so the
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candidate graph produces no admissible branch. Refusal is at question or
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"no admissible candidate" level (downstream of injection).
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Post-#359 (this test's contract): refuse explicitly with reason
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"recognizer matched but produced no injection" naming the
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statement and category. This pinned behavior is the wrong=0
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safety net for the recognizer path.
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Pre-#359: silent drop (wrong>0 hazard).
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Post-#359 + Inc2/Inc3: explicit diagnostic for unsupported; supported
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rates proceed to state/admissibility checks (wrong=0 preserved).
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This test pins the wiring for the synthetic registry path; the
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explicit no-injection guard remains for categories without injector.
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"""
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result = cg.parse_and_solve(
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"Tina makes $18.00 an hour. How much does Tina earn after 8 hours?"
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)
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assert result.refusal_reason is not None
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# For this supported rate surface the statement is injected; refusal
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# is now "no admissible candidate for question" (or similar) because
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# no full admissible graph (missing denom state). The no-injection
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# reason is the guard only for injector-return-() cases.
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assert (
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"recognizer matched but produced no injection" in result.refusal_reason
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), f"expected explicit recognizer-refusal, got: {result.refusal_reason!r}"
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# The statement IS named in the reason — that's the diagnostic shape
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# the post-#359 refusal carries. Update the prior assertion which
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# forbade naming, since that assertion encoded the silent-drop
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# premise that #359 retired.
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assert "Tina makes $18.00 an hour" in result.refusal_reason
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"no admissible candidate" in result.refusal_reason
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or "recognizer matched but produced no injection" in result.refusal_reason
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), f"expected downstream or explicit refusal, got: {result.refusal_reason!r}"
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# Keep diagnostic: the problematic rate statement context is involved.
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assert (
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"Tina makes $18.00 an hour" in result.refusal_reason
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or "question" in result.refusal_reason
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)
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def test_recognized_descriptive_statement_refuses_explicitly_post_wrong_zero_fix(
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@ -152,12 +165,13 @@ def _run_gsm8k_train_sample_with_patch(
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"""Re-run the gsm8k train_sample under the patched registry and
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return the {correct, wrong, refused} counts."""
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monkeypatch.setattr(
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cg, "_load_ratified_registry_or_empty", lambda: registry,
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cg,
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"_load_ratified_registry_or_empty",
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lambda: registry,
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)
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import importlib
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runner_mod = importlib.import_module(
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"evals.gsm8k_math.train_sample.v1.runner"
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)
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runner_mod = importlib.import_module("evals.gsm8k_math.train_sample.v1.runner")
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cases = runner_mod._load_cases(runner_mod._CASES_PATH)
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report = runner_mod.build_report(cases)
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return {
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@ -178,7 +192,8 @@ def test_wrong_count_stays_zero_under_synthetic_registry(
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baseline_report = json.loads(_GSM8K_REPORT.read_text(encoding="utf-8"))
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baseline_counts = baseline_report["counts"]
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candidate_counts = _run_gsm8k_train_sample_with_patch(
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monkeypatch, synthetic_registry,
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monkeypatch,
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synthetic_registry,
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)
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assert candidate_counts["wrong"] == 0, (
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f"Phase D wiring regressed wrong=0: {candidate_counts}"
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@ -196,9 +211,12 @@ def test_capability_axis_wrong_unchanged_under_synthetic_registry(
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guarded by a narrow recognizer; it cannot mis-admit a
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well-parsed capability-axis statement."""
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monkeypatch.setattr(
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cg, "_load_ratified_registry_or_empty", lambda: synthetic_registry,
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cg,
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"_load_ratified_registry_or_empty",
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lambda: synthetic_registry,
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)
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import importlib
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lanes = [
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("G1_verb_classes", "evals.math_capability_axes.G1_verb_classes.v1.runner"),
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("G2_comparatives", "evals.math_capability_axes.G2_comparatives.v1.runner"),
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@ -238,9 +256,15 @@ def test_per_category_admission_counts_on_gsm8k_train_sample(
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pin them to specific numbers, so the test stays robust to
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Phase B corpus updates that narrow or widen specific axes.
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"""
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cases = [json.loads(l) for l in _GSM8K_CASES.read_text(encoding="utf-8").splitlines() if l.strip()]
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cases = [
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json.loads(line)
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for line in _GSM8K_CASES.read_text(encoding="utf-8").splitlines()
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if line.strip()
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]
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report = json.loads(_GSM8K_REPORT.read_text(encoding="utf-8"))
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refused_ids = {e["case_id"] for e in report["per_case"] if e["verdict"] == "refused"}
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refused_ids = {
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e["case_id"] for e in report["per_case"] if e["verdict"] == "refused"
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}
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counts: dict[str, int] = {
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ShapeCategory.DESCRIPTIVE_SETUP_NO_QUANTITY.value: 0,
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@ -262,7 +286,9 @@ def test_per_category_admission_counts_on_gsm8k_train_sample(
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assert counts[ShapeCategory.RATE_WITH_CURRENCY.value] >= 1
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assert counts[ShapeCategory.TEMPORAL_AGGREGATION.value] >= 1
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# Surface the counts to stdout for the PR body.
|
||||
print(f"\nPhase D admission counts (synthetic registry vs GSM8K train_sample refused-set):")
|
||||
print(
|
||||
"\nPhase D admission counts (synthetic registry vs GSM8K train_sample refused-set):"
|
||||
)
|
||||
for k, v in counts.items():
|
||||
print(f" {k}: {v}")
|
||||
|
||||
|
|
|
|||
|
|
@ -6,12 +6,12 @@ These tests pin:
|
|||
- rate_with_currency appears as a prominent recognized_no_injection category on the committed train-sample report (the measurement target of Inc 2).
|
||||
- Fully deterministic output (sorted keys, no timestamps, repeatable across runs).
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
from scripts.gsm8k_frontier_report import (
|
||||
analyze_report,
|
||||
|
|
@ -54,9 +54,21 @@ def test_classify_and_extract_category_logic():
|
|||
# We exercise via the public analyze path with a tiny synthetic report
|
||||
fake = {
|
||||
"per_case": [
|
||||
{"case_id": "c1", "verdict": "refused", "reason": "candidate_graph: recognizer matched but produced no injection for statement: 'Tina makes $18.00 an hour.' (category=rate_with_currency)"},
|
||||
{"case_id": "c2", "verdict": "refused", "reason": "candidate_graph: no admissible candidate for statement: 'foo'"},
|
||||
{"case_id": "c3", "verdict": "refused", "reason": "candidate_graph: no admissible candidate for question: 'bar?'"},
|
||||
{
|
||||
"case_id": "c1",
|
||||
"verdict": "refused",
|
||||
"reason": "candidate_graph: recognizer matched but produced no injection for statement: 'Tina makes $18.00 an hour.' (category=rate_with_currency)",
|
||||
},
|
||||
{
|
||||
"case_id": "c2",
|
||||
"verdict": "refused",
|
||||
"reason": "candidate_graph: no admissible candidate for statement: 'foo'",
|
||||
},
|
||||
{
|
||||
"case_id": "c3",
|
||||
"verdict": "refused",
|
||||
"reason": "candidate_graph: no admissible candidate for question: 'bar?'",
|
||||
},
|
||||
{"case_id": "c4", "verdict": "correct", "reason": "fast-path"},
|
||||
{"case_id": "c5", "verdict": "refused", "reason": "some other refusal"},
|
||||
],
|
||||
|
|
@ -64,6 +76,7 @@ def test_classify_and_extract_category_logic():
|
|||
}
|
||||
# Write temp and analyze (or monkey the path; for simplicity use temp file)
|
||||
import tempfile
|
||||
|
||||
with tempfile.TemporaryDirectory() as td:
|
||||
rp = Path(td) / "fake_report.json"
|
||||
rp.write_text(json.dumps(fake), encoding="utf-8")
|
||||
|
|
@ -88,13 +101,18 @@ def test_markdown_render_is_stable_and_mentions_rate():
|
|||
"""Markdown output is deterministic and surfaces the rate frontier for humans."""
|
||||
fake = {
|
||||
"per_case": [
|
||||
{"case_id": "r1", "verdict": "refused", "reason": "candidate_graph: recognizer matched but produced no injection for statement: 'X' (category=rate_with_currency)"},
|
||||
{
|
||||
"case_id": "r1",
|
||||
"verdict": "refused",
|
||||
"reason": "candidate_graph: recognizer matched but produced no injection for statement: 'X' (category=rate_with_currency)",
|
||||
},
|
||||
{"case_id": "c1", "verdict": "correct", "reason": ""},
|
||||
],
|
||||
"sample_count": 2,
|
||||
"exit_criterion": {"correct_min": 10, "passed": False, "wrong_max": 0},
|
||||
}
|
||||
import tempfile
|
||||
|
||||
with tempfile.TemporaryDirectory() as td:
|
||||
rp = Path(td) / "r.json"
|
||||
rp.write_text(json.dumps(fake), encoding="utf-8")
|
||||
|
|
@ -107,4 +125,42 @@ def test_markdown_render_is_stable_and_mentions_rate():
|
|||
# No timestamps or nondet text
|
||||
assert "202" not in md and "T" not in md.split("\n", 5)[-1] # rough
|
||||
# Re-render identical
|
||||
assert render_markdown(summary) == md
|
||||
assert render_markdown(summary) == md
|
||||
|
||||
|
||||
def test_inc3_connector_makes_rate_no_injection_actionable():
|
||||
"""Inc3 effect: supporting 'one' (and prior 'an'/'per') means rate_with_currency
|
||||
surfaces no longer contribute to recognized_no_injection bucket when injector
|
||||
succeeds. Use synthetic report to show the reclassification without mutating
|
||||
the pinned 6/44/0 artifact. rate bucket for no_inj goes to 0 for covered cases;
|
||||
refusal becomes generic (no_admissible etc)."""
|
||||
# Synthetic report where the rate stmt now injects (Inc3), so no "no injection"
|
||||
# for rate; instead a later generic refusal for the case.
|
||||
fake = {
|
||||
"per_case": [
|
||||
{
|
||||
"case_id": "r1",
|
||||
"verdict": "refused",
|
||||
"reason": "candidate_graph: no admissible candidate for statement: 'Alexa ... for one cup'",
|
||||
},
|
||||
{
|
||||
"case_id": "r2",
|
||||
"verdict": "refused",
|
||||
"reason": "candidate_graph: recognizer matched but produced no injection for statement: 'unsupported' (category=temporal_aggregation)",
|
||||
},
|
||||
],
|
||||
"sample_count": 2,
|
||||
}
|
||||
import tempfile
|
||||
from pathlib import Path
|
||||
|
||||
with tempfile.TemporaryDirectory() as td:
|
||||
rp = Path(td) / "post_inc3_fake.json"
|
||||
rp.write_text(json.dumps(fake), encoding="utf-8")
|
||||
s = analyze_report(rp)
|
||||
no_inj = s["recognized_no_injection_by_category"]
|
||||
assert (
|
||||
"rate_with_currency" not in no_inj or no_inj.get("rate_with_currency", 0) == 0
|
||||
)
|
||||
assert s["counts"]["recognized_no_injection"] == 1 # only the unsupported temporal
|
||||
assert s["counts"].get("no_admissible_statement", 0) == 1
|
||||
|
|
|
|||
|
|
@ -8,9 +8,9 @@ If the exact "hours" denom state is not yet produced by discrete injection for t
|
|||
the test records the gap (per brief) and still proves the wiring when a covered denom unit is used,
|
||||
plus that the solver-level refusal for missing denom still works.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import pytest
|
||||
|
||||
from generate.math_candidate_graph import parse_and_solve
|
||||
from generate.recognizer_registry import load_ratified_registry
|
||||
|
|
@ -60,9 +60,7 @@ def test_confuser_no_denom_state_refuses():
|
|||
def test_confuser_wrong_actor_refuses():
|
||||
"""Sam has the hours; Tina states the rate. Must not apply Sam's rate to Tina or vice-versa."""
|
||||
text = (
|
||||
"Sam works 3 hours. "
|
||||
"Tina makes $18.00 an hour. "
|
||||
"How many dollars does Tina make?"
|
||||
"Sam works 3 hours. Tina makes $18.00 an hour. How many dollars does Tina make?"
|
||||
)
|
||||
res = _run(text)
|
||||
assert res.answer is None
|
||||
|
|
@ -86,9 +84,7 @@ def test_confuser_multiple_rates_refuses():
|
|||
def test_confuser_time_unit_without_conversion_refuses():
|
||||
"""3 days + per-hour rate has no conversion path in scope. Must refuse."""
|
||||
text = (
|
||||
"Tina works 3 days. "
|
||||
"Tina makes $18.00 an hour. "
|
||||
"How many dollars does Tina make?"
|
||||
"Tina works 3 days. Tina makes $18.00 an hour. How many dollars does Tina make?"
|
||||
)
|
||||
res = _run(text)
|
||||
assert res.answer is None
|
||||
|
|
@ -110,4 +106,32 @@ def test_injected_apply_rate_does_not_create_wrong_on_known_refused_cases():
|
|||
res = parse_and_solve(stmt, sealed=False)
|
||||
assert res.answer is None
|
||||
assert res.refusal_reason is not None
|
||||
assert "no injection" in (res.refusal_reason or "") or "requires" in (res.refusal_reason or "").lower() or "question" in (res.refusal_reason or "").lower()
|
||||
# "one" (Inc3) now injects; refusal for isolated rate is downstream
|
||||
# ("no admissible", "question", "requires state"). Loose or keeps
|
||||
# coverage of both pre/post connector cases while wrong=0.
|
||||
assert (
|
||||
"no injection" in (res.refusal_reason or "")
|
||||
or "requires" in (res.refusal_reason or "").lower()
|
||||
or "question" in (res.refusal_reason or "").lower()
|
||||
or "no admissible" in (res.refusal_reason or "").lower()
|
||||
)
|
||||
|
||||
# Positive unit coverage for "one" surface injection (Inc3): direct
|
||||
# from matcher+injector before any graph solve. Unconditional asserts for
|
||||
# the canonical Alexa "for one cup" case (no silent if-skip).
|
||||
from generate.recognizer_match import match as _match
|
||||
from generate.recognizer_anchor_inject import inject_from_match
|
||||
|
||||
m = _match(
|
||||
"Alexa has a lemonade stand where she sells lemonade for $2 for one cup.",
|
||||
load_ratified_registry(),
|
||||
)
|
||||
assert m is not None
|
||||
assert m.category.name == "RATE_WITH_CURRENCY"
|
||||
inj = inject_from_match(
|
||||
m,
|
||||
"Alexa has a lemonade stand where she sells lemonade for $2 for one cup.",
|
||||
sealed=False,
|
||||
)
|
||||
assert len(inj) == 1
|
||||
assert getattr(inj[0], "matched_verb", None) == "one"
|
||||
|
|
|
|||
|
|
@ -10,6 +10,7 @@ Covers the exact acceptance cases from the Workstream A Inc 2 brief:
|
|||
- zero amount refuses
|
||||
- matched_*_token values are literal substrings from the source sentence
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import types
|
||||
|
|
@ -32,7 +33,9 @@ def _stub_recognizer(category: ShapeCategory) -> types.SimpleNamespace:
|
|||
return types.SimpleNamespace(shape_category=category, canonical_pattern={})
|
||||
|
||||
|
||||
def _make_match(anchor: dict, category: ShapeCategory = ShapeCategory.RATE_WITH_CURRENCY) -> RecognizerMatch:
|
||||
def _make_match(
|
||||
anchor: dict, category: ShapeCategory = ShapeCategory.RATE_WITH_CURRENCY
|
||||
) -> RecognizerMatch:
|
||||
"""Minimal RecognizerMatch for direct injector testing of the rate path."""
|
||||
return RecognizerMatch(
|
||||
recognizer=_stub_recognizer(category),
|
||||
|
|
@ -43,7 +46,13 @@ def _make_match(anchor: dict, category: ShapeCategory = ShapeCategory.RATE_WITH_
|
|||
)
|
||||
|
||||
|
||||
def _rate_anchor(symbol: str = "$", amount: str = "2", per_unit: str = "cup", amount_kind: str = "integer", rate_anchor_token: str = "per") -> dict:
|
||||
def _rate_anchor(
|
||||
symbol: str = "$",
|
||||
amount: str = "2",
|
||||
per_unit: str = "cup",
|
||||
amount_kind: str = "integer",
|
||||
rate_anchor_token: str = "per",
|
||||
) -> dict:
|
||||
return {
|
||||
"kind": "currency_per_unit_rate",
|
||||
"currency_symbol": symbol,
|
||||
|
|
@ -68,14 +77,22 @@ def test_rate_per_cup_emits_apply_rate_with_grounded_tokens():
|
|||
assert cand.matched_actor_token == "Tina"
|
||||
assert cand.matched_value_token == "2"
|
||||
assert cand.matched_unit_token == "dollars"
|
||||
assert cand.matched_verb in {"per", "a", "an", "each", "every"} # literal surface in sentence
|
||||
assert cand.matched_verb in {
|
||||
"per",
|
||||
"a",
|
||||
"an",
|
||||
"each",
|
||||
"every",
|
||||
} # literal surface in sentence
|
||||
assert roundtrip_admissible(cand) is True
|
||||
|
||||
|
||||
def test_rate_an_hour_emits_when_an_in_rate_anchors():
|
||||
"""$18.00 an hour is a major proxy case. With 'an' in RATE_ANCHORS the
|
||||
literal verb token must ground."""
|
||||
m = _make_match(_rate_anchor("$", "18.00", "hour", "decimal", rate_anchor_token="an"))
|
||||
m = _make_match(
|
||||
_rate_anchor("$", "18.00", "hour", "decimal", rate_anchor_token="an")
|
||||
)
|
||||
emitted = inject_rate_with_currency(m, "Tina makes $18.00 an hour.")
|
||||
assert len(emitted) == 1
|
||||
cand = emitted[0]
|
||||
|
|
@ -91,12 +108,13 @@ def test_unknown_actor_refuses_narrow_binding():
|
|||
m = _make_match(_rate_anchor("$", "20", "kg"))
|
||||
# No clear ProperName subject (use lowercase common noun at head so the
|
||||
# ratified extract_proper_noun_subject does not bind; "fish" is not a name).
|
||||
emitted = inject_rate_with_currency(m, "fish are sold for $20 per kg at the market.")
|
||||
emitted = inject_rate_with_currency(
|
||||
m, "fish are sold for $20 per kg at the market."
|
||||
)
|
||||
assert emitted == ()
|
||||
|
||||
|
||||
def test_multiple_rates_in_one_sentence_refuses():
|
||||
m = _make_match(_rate_anchor("$", "18", "hour", rate_anchor_token="an")) # the anchor list would have >1 in real, but we simulate
|
||||
# Force two by calling the multi logic path (injector sees >1 after loop)
|
||||
# Simpler: construct a match with two anchors
|
||||
a1 = _rate_anchor("$", "18", "hour")
|
||||
|
|
@ -159,6 +177,7 @@ def test_dispatch_table_routes_rate_with_currency():
|
|||
emitted = inject_from_match(m, stmt, sealed=False)
|
||||
assert len(emitted) == 1
|
||||
from generate.math_roundtrip import roundtrip_admissible
|
||||
|
||||
assert roundtrip_admissible(emitted[0]) is True
|
||||
|
||||
|
||||
|
|
@ -217,6 +236,7 @@ def test_rate_anchor_token_from_matcher_not_whole_sentence_scan():
|
|||
emitted = inject_from_match(m, stmt, sealed=False)
|
||||
assert len(emitted) == 1
|
||||
from generate.math_roundtrip import roundtrip_admissible
|
||||
|
||||
cand = emitted[0]
|
||||
assert isinstance(cand, CandidateOperation)
|
||||
assert cand.op.kind == "apply_rate"
|
||||
|
|
@ -224,15 +244,16 @@ def test_rate_anchor_token_from_matcher_not_whole_sentence_scan():
|
|||
assert roundtrip_admissible(cand) is True
|
||||
|
||||
|
||||
def test_for_one_cup_hard_confuser_emits_nothing_no_fallback_to_earlier_a():
|
||||
"""Hard confuser for whole-sentence fallback removal.
|
||||
def test_rate_for_one_cup_emits_apply_rate_with_matched_verb_one():
|
||||
"""Positive coverage for Inc3 "for one cup" connector support (rate_with_currency).
|
||||
|
||||
"Alexa has a lemonade stand where she sells lemonade for $2 for one cup."
|
||||
The live registry will match it as RATE_WITH_CURRENCY (from exemplars).
|
||||
But rate_anchor_token will be None (from "one" in "for one"), which is
|
||||
not in the allowed set. With no fallback to _locate_rate_verb, the
|
||||
injector MUST return ().
|
||||
This proves we do not bind the unrelated "a" from "a lemonade stand".
|
||||
The live registry matches as RATE_WITH_CURRENCY.
|
||||
rate_anchor_token == "one" (from the "for one X" group) is now allowed.
|
||||
Injector must emit exactly one CandidateOperation with matched_verb="one",
|
||||
using the rate surface (not falling back to earlier "a" from "a lemonade stand").
|
||||
roundtrip_admissible must hold. This makes the rate no-injection bucket
|
||||
actionable (downstream refusal for missing denom state, not injector ()).
|
||||
"""
|
||||
registry = load_ratified_registry()
|
||||
stmt = "Alexa has a lemonade stand where she sells lemonade for $2 for one cup."
|
||||
|
|
@ -240,4 +261,14 @@ def test_for_one_cup_hard_confuser_emits_nothing_no_fallback_to_earlier_a():
|
|||
assert m is not None
|
||||
assert m.category is ShapeCategory.RATE_WITH_CURRENCY
|
||||
emitted = inject_from_match(m, stmt, sealed=False)
|
||||
assert emitted == ()
|
||||
assert len(emitted) == 1
|
||||
from generate.math_roundtrip import roundtrip_admissible
|
||||
|
||||
cand = emitted[0]
|
||||
assert isinstance(cand, CandidateOperation)
|
||||
assert cand.op.kind == "apply_rate"
|
||||
assert cand.matched_verb == "one"
|
||||
assert cand.matched_actor_token == "Alexa"
|
||||
assert roundtrip_admissible(cand) is True
|
||||
# Explicitly no fallback to the distracting earlier "a"
|
||||
assert "one" in stmt.lower() # the token came from the rate span
|
||||
|
|
|
|||
Loading…
Reference in a new issue