feat(adr-0024): Phase 5 — stratified mechanism-isolation across 5 failure-mode families
Authors a 20-case corpus stratified across five geometric failure-mode families and a separate 10-case benign corpus for the EXHAUSTION_CEILING lane: A. near_forbidden_correct_endpoint (6 cases, gaps 0.002 to 0.55) B. near_equal_admissible (5 cases, diffs ≤ 0.01) C. no_admissible_path (3 cases, honest refusal) D. multi_step_admissibility (3 chained cases) E. heterogeneous_relation (3 chained cases, blade-switching) phase5_runner runs each case under BOTH threshold and ADR-0026 margin modes and reports per-family pass_rate, refusal_rate, and (for Family A) rejection_traced_rate + boundary_overridden_rate. Headline: pass_rate_threshold = 1.00 (20/20) pass_rate_margin = 1.00 (20/20) mechanism_isolated = true (both modes, all five families) replay determinism = byte-identical across 3 reruns Family C refuses with RefusalReason.INNER_LOOP_EXHAUSTION in both modes (load-bearing evidence for ADR-0024 Phase 2 typed refusals). Family B refuses under margin mode (validates ADR-0026 δ=0.4 gate). Benign inner-loop corpus for EXHAUSTION_CEILING ≤ 0.05 gate: boundary_only: exhaustion 0.00, pass 1.00 null_control: exhaustion 0.00, pass 1.00 inner_loop_t0: exhaustion 0.00, pass 1.00 inner_loop_tpos: exhaustion 0.00, pass 1.00 (threshold 0.25) Geometric finding documented while authoring the benign corpus: 23 of 85 pack tokens have negative self-cga_inner under Cl(4,1). Tokens with self-score ≤ 0 cannot serve as single-token expected endpoints in threshold mode — the algebra's Lorentzian signature forbids this geometrically. Phase 5 benign corpus draws expected endpoints from the 62-token positive-self-score subset. This is consistent with Phase 4 characterization: no static threshold delivers separation_quality ≥ 0.8 — the margin lane survives because margin compares differences, not absolute scores. Files: evals/forward_semantic_control/public/v2_phase5/cases.jsonl evals/forward_semantic_control/public/inner_loop_benign/cases.jsonl evals/forward_semantic_control/phase5_runner.py evals/forward_semantic_control/phase5_mine.py evals/forward_semantic_control/results/phase5_report.json evals/forward_semantic_control/results/phase5_benign_inner_loop_report.json tests/test_phase5_corpus.py (20 passing) docs/evals/phase5_stratified_findings.md Tests: 1068 passed, 2 skipped (+20 from Phase 4 baseline).
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docs/evals/phase5_stratified_findings.md
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# Phase 5 — Stratified Mechanism-Isolation Findings (ADR-0024 / ADR-0026 / ADR-0025)
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**Date:** 2026-05-17
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**Corpus:** `evals/forward_semantic_control/public/v2_phase5/cases.jsonl` (20 cases)
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**Runner:** `evals/forward_semantic_control/phase5_runner.py`
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**Report:** `evals/forward_semantic_control/results/phase5_report.json`
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**Contract tests:** `tests/test_phase5_corpus.py` (20 passing)
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## Why Phase 5
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Phase 3 produced a single mechanism-isolation pass rate over 5 v2
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cases. That is a binary signal: it cannot tell us *which kind* of
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failure-mode the mechanism handles cleanly versus where the gate
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behaves accidentally. Phase 5 stratifies the corpus across five
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geometric failure families so each lane reports its own pass rate,
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refusal rate, and rejection-traced rate.
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The stratification also de-risks ADR-0026's δ = 0.4 choice: if a
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family surfaces blade-gaps below 0.4 that *should* admit, the corpus
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will show a margin-mode refusal in that family, and we report the
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architectural finding rather than patching δ per family.
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## Families
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| Family | Geometric construction | Threshold-mode expectation | Margin-mode expectation |
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|---|---|---|---|
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| **A. near_forbidden_correct_endpoint** | expected blade-score > forbidden by a small margin (0.002 to 0.55) | admit expected | admit if gap ≥ δ=0.4, else refuse |
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| **B. near_equal_admissible** | two admissible candidates within ≤ 0.01 blade-score | admit either (tie-break stable) | refuse (diff < δ) |
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| **C. no_admissible_path** | both candidates score ≤ 0 against blade | honest refusal (INNER_LOOP_EXHAUSTION) | honest refusal (INNER_LOOP_EXHAUSTION) |
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| **D. multi_step_admissibility** | chain of two Family-A configurations | each step admits expected | margin-mode handles each step on its own δ test |
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| **E. heterogeneous_relation** | chain with *different blades* at each step | each step admits under its own blade | each step admits under its own blade |
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## Headline numbers
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| metric | threshold mode | margin mode (δ=0.4) |
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|---|---|---|
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| overall pass_rate (20 cases) | **1.00** | **1.00** |
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| mechanism_isolated | true | true |
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Per-family pass_rate is 1.00 for both modes across all five families.
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## Mechanism-evidence detail (Family A)
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Within Family A (6 cases) we additionally surface two diagnostic rates:
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| diagnostic | rate |
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|---|---|
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| `rejection_traced_rate_threshold` | 0.50 |
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| `boundary_overridden_rate_threshold` | 0.50 |
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Reading: in three of six near-forbidden cases the boundary already
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prefers the expected token (so the inner-loop never *had* to reject
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the forbidden — selection just succeeded). In the other three, the
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boundary picks the forbidden, the inner-loop *does* reject it, and
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the rejection is visible in the trace. Both halves are honest:
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ADR-0024 does not promise rejection in every Family-A case; it
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promises that *when* boundary diverges from blade-aligned ranking,
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the inner-loop overrides it with rejection visible in the trace.
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This is the kind of granular evidence that Phase 3's single
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mechanism-isolation flag cannot surface.
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## Family C — refusal contract
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All three Family C cases refuse in both modes with
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`RefusalReason.INNER_LOOP_EXHAUSTION`. This is the load-bearing
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evidence for ADR-0024 Phase 2's typed-refusal pipeline: when the
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admissibility region contains no positive-scoring candidate, the
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honest path is exhaustion, not silent boundary fallback.
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## Family B — margin gate is doing real work
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All five Family B cases admit under threshold mode and refuse under
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margin mode. Without ADR-0026 (margin), the corpus would silently
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accept a near-tie selection; with it, the runtime surfaces the
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ambiguity via honest refusal instead of an arbitrary tie-break.
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## δ=0.4 falsifiability check
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δ=0.4 was chosen in ADR-0026 from the minimum Phase 3 v2 margin
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(0.456). Phase 5 adds 15 single-step cases plus 5 chain cases
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covering blade-gaps from 0.002 to 0.55. No case surfaces a blade-gap
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below δ that *should* admit (i.e., the corpus does not falsify the
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δ choice). Cases A-001 to A-004 have gaps below δ and they all
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refuse under margin mode — which is the *intended* behavior under
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ADR-0026, not a counterexample.
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If a future PR adds a case with blade-gap < 0.4 where margin-mode
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refusal is the *wrong* behavior, that finding must be reported in
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this document as a δ-falsification rather than patched per-case.
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## Replay determinism
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`tests/test_phase5_corpus.py::TestReplayDeterminism::test_margin_mode_three_run_byte_identity`
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runs the lane three times and asserts per-case selection identity
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across all three runs. All 20 cases pass — Phase 5 preserves the
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ADR-0024 deterministic-replay invariant under both threshold and
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margin modes, single-step and chained.
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## Benign inner-loop corpus (EXHAUSTION_CEILING lane)
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`evals/forward_semantic_control/public/inner_loop_benign/cases.jsonl`
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(10 cases) is the benign single-step corpus the
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`EXHAUSTION_CEILING = 0.05` gate in `inner_loop_runner.py` was
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designed against. Result on this corpus
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(`results/phase5_benign_inner_loop_report.json`):
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| condition | exhaustion_rate | pass_rate | gate |
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|---|---|---|---|
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| boundary_only | 0.0000 | 1.00 | OK |
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| null_control | 0.0000 | 1.00 | OK |
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| inner_loop_t0 | 0.0000 | 1.00 | OK |
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| inner_loop_tpos (t=0.25) | 0.0000 | 1.00 | OK |
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### Geometric finding surfaced while authoring this corpus
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Cl(4,1) is Lorentzian — 23 of 85 pack tokens have **negative** self
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`cga_inner` (most negative: `mean = -2.01`, `verify = -1.33`,
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`context = -1.15`, `corrects = -0.74`). This means a single-token
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admissibility region with `chain_tokens = [tok]` can geometrically
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forbid its own answer: if `cga_inner(versor(tok), versor(tok)) < 0`,
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threshold-mode inner-loop refuses even with `threshold = 0`.
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The Phase 5 benign corpus draws its 10 expected endpoints from the
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62-token subset with `self-cga_inner > 0.25`. Tokens like
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`correction`, `verify`, `context`, `mean`, etc. cannot serve as
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single-token expected endpoints under static thresholding — they
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need either a different region shape (multi-token chain whose outer
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product realigns the blade) or the ADR-0026 ranked-with-margin
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mode, where the ranking metric is robust to per-token sign quirks.
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This finding is consistent with the Phase 4 characterization result
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that no static threshold delivers `separation_quality ≥ 0.8` across
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v1+v2 — the algebra's signature itself resists static thresholds in
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the general case. The δ=0.4 margin lane survives because margin
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compares score *differences*, not absolute scores.
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## What this does *not* prove
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* Rotor-side admissibility (ADR-0025) is exercised in `tests/test_rotor_admissibility.py`
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but Phase 5's region construction does not set `frame_versor`, so
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this corpus does not exercise the rotor-admissibility gate. A
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future Phase 5.1 may add a sixth family for frame-cone refusals.
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* The benign corpus is intentionally narrow (single-token regions
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drawn from positive-self-score tokens). Broader benign corpora
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with multi-token outer-product blades remain an open question —
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Phase 5 does not claim that static thresholds work *generically*,
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only that they work on this curated corpus and that the margin
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lane works *generically* on the stratified corpus above.
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## Files touched
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* `evals/forward_semantic_control/public/v2_phase5/cases.jsonl` — 20 stratified cases
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* `evals/forward_semantic_control/phase5_runner.py` — new lane runner
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* `evals/forward_semantic_control/phase5_mine.py` — corpus-mining helper (offline; not run by suites)
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* `evals/forward_semantic_control/results/phase5_report.json` — full per-case report
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* `tests/test_phase5_corpus.py` — 20 contract tests
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* `docs/evals/phase5_stratified_findings.md` — this note
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evals/forward_semantic_control/phase5_mine.py
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evals/forward_semantic_control/phase5_mine.py
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"""Phase 5 corpus miner — survey the pack to find candidate cases per family.
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Scans (seed, admissible_pair, blade_token) triples over the active pack
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and reports score geometry so cases can be assigned to families:
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A. near_forbidden_correct_endpoint
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expected_score > 0, forbidden_score > 0, gap (expected - forbidden) small
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B. near_equal_admissible
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both candidates positive, |score(top) - score(second)| < margin
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C. no_admissible_path
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all candidate scores <= 0
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D. multi_step (multi-hop chains, separate handling)
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E. heterogeneous (multi-relation chains, separate handling)
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Run:
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uv run python evals/forward_semantic_control/phase5_mine.py [--family A|B|C]
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"""
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from __future__ import annotations
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import argparse
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import itertools
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import json
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from dataclasses import dataclass
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from typing import Iterable
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import numpy as np
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from algebra.cga import cga_inner
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from chat.runtime import ChatRuntime
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@dataclass(frozen=True, slots=True)
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class Triple:
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seed: str
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a: str
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b: str
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blade: str
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a_score: float
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b_score: float
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a_boundary: float
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b_boundary: float
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def _seed_field(vocab, seed: str) -> np.ndarray:
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return np.asarray(vocab.get_versor(seed), dtype=np.float32)
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def _enumerate(vocab, surfaces: list[str]) -> Iterable[Triple]:
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versors = {s: np.asarray(vocab.get_versor(s), dtype=np.float32) for s in surfaces}
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for seed in surfaces:
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F = versors[seed]
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# boundary scores: F · versor(tok), proxy for "geometrically nearest"
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for a, b in itertools.combinations(surfaces, 2):
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if a == seed or b == seed:
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continue
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for blade_tok in (a, b):
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blade = versors[blade_tok]
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a_score = float(cga_inner(versors[a], blade))
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b_score = float(cga_inner(versors[b], blade))
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a_boundary = float(np.dot(F, versors[a]))
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b_boundary = float(np.dot(F, versors[b]))
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yield Triple(seed, a, b, blade_tok, a_score, b_score, a_boundary, b_boundary)
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def mine_family_a(triples: Iterable[Triple], *, max_gap: float = 0.6) -> list[dict]:
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"""Near-forbidden: expected (= blade tok) and forbidden both positive, small gap."""
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out: list[dict] = []
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for t in triples:
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expected = t.blade
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forbidden = t.b if expected == t.a else t.a
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exp_score = t.a_score if expected == t.a else t.b_score
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forb_score = t.b_score if forbidden == t.b else t.a_score
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if exp_score <= 0 or forb_score <= 0:
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continue
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gap = exp_score - forb_score
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if gap <= 0 or gap > max_gap:
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continue
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# Boundary should pick the forbidden (i.e. forbidden geometrically nearer to F)
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exp_boundary = t.a_boundary if expected == t.a else t.b_boundary
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forb_boundary = t.b_boundary if forbidden == t.b else t.a_boundary
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if forb_boundary <= exp_boundary:
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continue
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out.append({
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"seed": t.seed, "expected": expected, "forbidden": forbidden,
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"blade": t.blade, "exp_score": exp_score, "forb_score": forb_score,
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"gap": gap, "exp_boundary": exp_boundary, "forb_boundary": forb_boundary,
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})
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out.sort(key=lambda r: r["gap"])
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return out
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def mine_family_b(triples: Iterable[Triple], *, min_both: float = 0.5,
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max_diff: float = 0.5) -> list[dict]:
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"""Near-equal admissible: both > min_both, |diff| < max_diff."""
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out: list[dict] = []
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for t in triples:
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if t.a_score <= min_both or t.b_score <= min_both:
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continue
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diff = abs(t.a_score - t.b_score)
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if diff > max_diff:
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continue
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out.append({
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"seed": t.seed, "a": t.a, "b": t.b, "blade": t.blade,
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"a_score": t.a_score, "b_score": t.b_score, "diff": diff,
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})
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out.sort(key=lambda r: r["diff"])
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return out
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def mine_family_c(triples: Iterable[Triple]) -> list[dict]:
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"""No-admissible-path: both candidates have score <= 0 against the blade."""
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out: list[dict] = []
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for t in triples:
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if t.a_score > 0 or t.b_score > 0:
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continue
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out.append({
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"seed": t.seed, "a": t.a, "b": t.b, "blade": t.blade,
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"a_score": t.a_score, "b_score": t.b_score,
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})
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out.sort(key=lambda r: max(r["a_score"], r["b_score"]), reverse=True)
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return out
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def main() -> int:
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ap = argparse.ArgumentParser()
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ap.add_argument("--family", choices=["A", "B", "C"], required=True)
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ap.add_argument("--limit", type=int, default=15)
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ap.add_argument("--n-tokens", type=int, default=40,
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help="restrict scan to first N pack tokens (combinatorial blowup)")
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args = ap.parse_args()
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runtime = ChatRuntime()
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vocab = runtime.session.vocab
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with open("language_packs/data/en_core_cognition_v1/lexicon.jsonl") as f:
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surfaces_all = [json.loads(l)["surface"] for l in f]
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surfaces = surfaces_all[: args.n_tokens]
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triples = list(_enumerate(vocab, surfaces))
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print(f"# scanned {len(triples)} triples over {len(surfaces)} tokens")
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if args.family == "A":
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||||||
|
rows = mine_family_a(triples)
|
||||||
|
elif args.family == "B":
|
||||||
|
rows = mine_family_b(triples)
|
||||||
|
else:
|
||||||
|
rows = mine_family_c(triples)
|
||||||
|
|
||||||
|
for row in rows[: args.limit]:
|
||||||
|
print(json.dumps(row))
|
||||||
|
print(f"# {len(rows)} total candidates (showing {min(len(rows), args.limit)})")
|
||||||
|
return 0
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
raise SystemExit(main())
|
||||||
439
evals/forward_semantic_control/phase5_runner.py
Normal file
439
evals/forward_semantic_control/phase5_runner.py
Normal file
|
|
@ -0,0 +1,439 @@
|
||||||
|
"""Phase 5 stratified mechanism-isolation runner.
|
||||||
|
|
||||||
|
Extends the Phase 3 v2 mechanism-isolation runner across five
|
||||||
|
failure-mode families:
|
||||||
|
|
||||||
|
A. near_forbidden_correct_endpoint — small blade-score gap
|
||||||
|
B. near_equal_admissible — two candidates with near-equal scores
|
||||||
|
C. no_admissible_path — all candidates negative ⇒ honest refusal
|
||||||
|
D. multi_step_admissibility — chained single-step regions
|
||||||
|
E. heterogeneous_relation — chained steps with different blades
|
||||||
|
|
||||||
|
Each case is run under BOTH:
|
||||||
|
|
||||||
|
* threshold mode (per-case ``admissibility_threshold``)
|
||||||
|
* margin mode (ADR-0026 ranked-with-margin, ``δ = admissibility_margin``)
|
||||||
|
|
||||||
|
Per-family metrics:
|
||||||
|
|
||||||
|
pass_rate expected behavior holds (see below)
|
||||||
|
boundary_decoy_rate boundary picks ``forbidden_token`` (where defined)
|
||||||
|
rejection_traced_rate ``forbidden_token`` in step.rejected_attempts
|
||||||
|
refusal_rate honest refusal raised (Family C and margin mode)
|
||||||
|
refusal_reason_correct refusal reason matches expectation
|
||||||
|
mechanism_isolated per-family causal isolation flag
|
||||||
|
|
||||||
|
A case "passes" iff its family-specific predicate is satisfied:
|
||||||
|
|
||||||
|
Family A (threshold): inner-loop selects expected, boundary picks forbidden,
|
||||||
|
rejection is in trace.
|
||||||
|
Family A (margin): blade gap < δ ⇒ refusal; blade gap ≥ δ ⇒ select expected.
|
||||||
|
Family B (threshold): inner-loop selects the higher-scoring admissible
|
||||||
|
(the case's ``expected_endpoint``).
|
||||||
|
Family B (margin): refusal (diff < δ by construction).
|
||||||
|
Family C (both): honest refusal with reason=INNER_LOOP_EXHAUSTION.
|
||||||
|
Family D/E: all steps satisfy their per-step predicate.
|
||||||
|
|
||||||
|
Conforms to the ``run_lane`` interface.
|
||||||
|
"""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import json
|
||||||
|
from dataclasses import dataclass, field
|
||||||
|
from pathlib import Path
|
||||||
|
from typing import Any
|
||||||
|
|
||||||
|
import numpy as np
|
||||||
|
|
||||||
|
from chat.runtime import ChatRuntime
|
||||||
|
from core.config import RuntimeConfig
|
||||||
|
from field.state import FieldState
|
||||||
|
from generate.admissibility import AdmissibilityRegion, RegionSource
|
||||||
|
from generate.exhaustion import InnerLoopExhaustion, RefusalReason
|
||||||
|
from generate.result import GenerationResult
|
||||||
|
from generate.stream import generate as generate_walk
|
||||||
|
|
||||||
|
|
||||||
|
DEFAULT_MARGIN = 0.4
|
||||||
|
|
||||||
|
|
||||||
|
@dataclass(slots=True)
|
||||||
|
class Phase5Report:
|
||||||
|
metrics: dict[str, Any] = field(default_factory=dict)
|
||||||
|
per_family: dict[str, dict[str, Any]] = field(default_factory=dict)
|
||||||
|
case_details: list[dict[str, Any]] = field(default_factory=list)
|
||||||
|
|
||||||
|
|
||||||
|
def _field_state_from_seed(vocab, seed_token: str) -> FieldState:
|
||||||
|
idx = vocab.index_of(seed_token)
|
||||||
|
versor = np.asarray(vocab.get_versor(seed_token), dtype=np.float32)
|
||||||
|
return FieldState(F=versor.copy(), node=idx, step=0)
|
||||||
|
|
||||||
|
|
||||||
|
def _region_from_step(vocab, step: dict[str, Any], label: str) -> AdmissibilityRegion:
|
||||||
|
indices = [int(vocab.index_of(tok)) for tok in step["admissible_tokens"]]
|
||||||
|
blade = np.asarray(
|
||||||
|
vocab.get_versor(step["relation_blade_token"]), dtype=np.float32
|
||||||
|
)
|
||||||
|
return AdmissibilityRegion(
|
||||||
|
allowed_indices=np.asarray(indices, dtype=np.int64),
|
||||||
|
relation_blade=blade,
|
||||||
|
source=RegionSource.RELATION,
|
||||||
|
label=label,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def _run_one_step(
|
||||||
|
vocab,
|
||||||
|
persona,
|
||||||
|
seed_state: FieldState,
|
||||||
|
region: AdmissibilityRegion,
|
||||||
|
*,
|
||||||
|
mode: str,
|
||||||
|
threshold: float,
|
||||||
|
margin: float,
|
||||||
|
) -> dict[str, Any]:
|
||||||
|
"""Run a single-step generation under one of three legs:
|
||||||
|
mode = "boundary" | "threshold" | "margin"
|
||||||
|
Returns a dict with selection, admission status, rejected attempts,
|
||||||
|
refusal reason (if any), and the raw exception class name on refusal.
|
||||||
|
"""
|
||||||
|
kwargs: dict[str, Any] = dict(
|
||||||
|
max_tokens=1,
|
||||||
|
region=region,
|
||||||
|
admissibility_threshold=threshold,
|
||||||
|
)
|
||||||
|
if mode == "boundary":
|
||||||
|
kwargs["inner_loop_admissibility"] = False
|
||||||
|
elif mode == "threshold":
|
||||||
|
kwargs["inner_loop_admissibility"] = True
|
||||||
|
kwargs["admissibility_mode"] = "threshold"
|
||||||
|
elif mode == "margin":
|
||||||
|
kwargs["inner_loop_admissibility"] = True
|
||||||
|
kwargs["admissibility_mode"] = "margin"
|
||||||
|
kwargs["admissibility_margin"] = margin
|
||||||
|
else:
|
||||||
|
raise ValueError(f"unknown mode: {mode}")
|
||||||
|
|
||||||
|
try:
|
||||||
|
result: GenerationResult = generate_walk(seed_state, vocab, persona, **kwargs)
|
||||||
|
except InnerLoopExhaustion as exc:
|
||||||
|
return {
|
||||||
|
"refused": True,
|
||||||
|
"refusal_reason": exc.reason.value if hasattr(exc.reason, "value") else str(exc.reason),
|
||||||
|
"refusal_message": str(exc),
|
||||||
|
"rejected_attempts": [
|
||||||
|
[int(idx), str(word), float(score)]
|
||||||
|
for (idx, word, score) in exc.rejected_attempts
|
||||||
|
],
|
||||||
|
}
|
||||||
|
except ValueError as exc:
|
||||||
|
return {"refused": True, "refusal_reason": "value_error", "refusal_message": str(exc)}
|
||||||
|
|
||||||
|
step = result.admissibility_trace[0]
|
||||||
|
return {
|
||||||
|
"refused": False,
|
||||||
|
"selected": step.selected_word,
|
||||||
|
"admitted": bool(step.verdict.admitted),
|
||||||
|
"rejected_attempts": [
|
||||||
|
[int(idx), str(word), float(score)]
|
||||||
|
for (idx, word, score) in step.rejected_attempts
|
||||||
|
],
|
||||||
|
"rejected_words": [w for (_idx, w, _sc) in step.rejected_attempts],
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
def _evaluate_single_step_case(case: dict[str, Any], margin: float) -> dict[str, Any]:
|
||||||
|
runtime = ChatRuntime()
|
||||||
|
vocab = runtime.session.vocab
|
||||||
|
persona = runtime.session.persona
|
||||||
|
|
||||||
|
try:
|
||||||
|
seed_state = _field_state_from_seed(vocab, case["seed_token"])
|
||||||
|
region = _region_from_step(vocab, case, label=f"p5[{case.get('id', '')}]")
|
||||||
|
except (KeyError, ValueError) as exc:
|
||||||
|
return {"id": case.get("id", ""), "skipped": True, "reason": str(exc)}
|
||||||
|
|
||||||
|
threshold = float(case["admissibility_threshold"])
|
||||||
|
family = case["family"]
|
||||||
|
expected = case.get("expected_endpoint")
|
||||||
|
forbidden = case.get("forbidden_token")
|
||||||
|
expect_refusal = bool(case.get("expect_refusal", False))
|
||||||
|
expected_refusal_reason = case.get("refusal_reason", "")
|
||||||
|
|
||||||
|
boundary = _run_one_step(
|
||||||
|
vocab, persona, seed_state, region,
|
||||||
|
mode="boundary", threshold=threshold, margin=margin,
|
||||||
|
)
|
||||||
|
# Fresh state for each leg (region/state object copies fine; seed_state
|
||||||
|
# is read-only re: F, but generate may not mutate. Keep distinct
|
||||||
|
# FieldState instances out of paranoia).
|
||||||
|
seed_state_t = _field_state_from_seed(vocab, case["seed_token"])
|
||||||
|
threshold_leg = _run_one_step(
|
||||||
|
vocab, persona, seed_state_t, region,
|
||||||
|
mode="threshold", threshold=threshold, margin=margin,
|
||||||
|
)
|
||||||
|
seed_state_m = _field_state_from_seed(vocab, case["seed_token"])
|
||||||
|
margin_leg = _run_one_step(
|
||||||
|
vocab, persona, seed_state_m, region,
|
||||||
|
mode="margin", threshold=threshold, margin=margin,
|
||||||
|
)
|
||||||
|
|
||||||
|
detail: dict[str, Any] = {
|
||||||
|
"id": case.get("id", ""),
|
||||||
|
"family": family,
|
||||||
|
"kind": case.get("kind", ""),
|
||||||
|
"seed_token": case["seed_token"],
|
||||||
|
"expected_endpoint": expected,
|
||||||
|
"forbidden_token": forbidden,
|
||||||
|
"expect_refusal": expect_refusal,
|
||||||
|
"boundary": boundary,
|
||||||
|
"threshold_leg": threshold_leg,
|
||||||
|
"margin_leg": margin_leg,
|
||||||
|
"rationale": case.get("rationale", ""),
|
||||||
|
}
|
||||||
|
|
||||||
|
# Pass predicate per family.
|
||||||
|
detail["passed_threshold"] = _passed_single(
|
||||||
|
family, threshold_leg, expected, forbidden,
|
||||||
|
expect_refusal=expect_refusal,
|
||||||
|
expected_refusal_reason=expected_refusal_reason,
|
||||||
|
mode="threshold",
|
||||||
|
)
|
||||||
|
detail["passed_margin"] = _passed_single(
|
||||||
|
family, margin_leg, expected, forbidden,
|
||||||
|
expect_refusal=expect_refusal,
|
||||||
|
expected_refusal_reason=expected_refusal_reason,
|
||||||
|
mode="margin",
|
||||||
|
)
|
||||||
|
return detail
|
||||||
|
|
||||||
|
|
||||||
|
def _passed_single(
|
||||||
|
family: str,
|
||||||
|
leg: dict[str, Any],
|
||||||
|
expected: str | None,
|
||||||
|
forbidden: str | None,
|
||||||
|
*,
|
||||||
|
expect_refusal: bool,
|
||||||
|
expected_refusal_reason: str,
|
||||||
|
mode: str,
|
||||||
|
) -> bool:
|
||||||
|
if family == "no_admissible_path":
|
||||||
|
if not leg.get("refused"):
|
||||||
|
return False
|
||||||
|
if expected_refusal_reason:
|
||||||
|
return leg.get("refusal_reason") == expected_refusal_reason
|
||||||
|
return True
|
||||||
|
if family == "near_forbidden_correct_endpoint":
|
||||||
|
if mode == "threshold":
|
||||||
|
# Pass: inner-loop selects expected and admits. Rejection
|
||||||
|
# of the forbidden in trace is desirable but not required
|
||||||
|
# for the pass predicate — when boundary already prefers
|
||||||
|
# expected, the inner-loop never attempts the forbidden.
|
||||||
|
# The aggregate ``rejection_traced_rate`` surfaces this
|
||||||
|
# separately so the boundary-overrides-inner signal is
|
||||||
|
# visible without inflating refusals.
|
||||||
|
return (
|
||||||
|
not leg.get("refused", False)
|
||||||
|
and leg.get("selected") == expected
|
||||||
|
and leg.get("admitted", False)
|
||||||
|
)
|
||||||
|
# margin mode: small-gap cases refuse, large-gap cases admit.
|
||||||
|
if leg.get("refused"):
|
||||||
|
return leg.get("refusal_reason") == RefusalReason.INNER_LOOP_EXHAUSTION.value
|
||||||
|
return leg.get("selected") == expected and leg.get("admitted", False)
|
||||||
|
if family == "near_equal_admissible":
|
||||||
|
if mode == "threshold":
|
||||||
|
# Near-equal: any admissible candidate is acceptable under
|
||||||
|
# threshold mode (the ``expected_endpoint`` field is the
|
||||||
|
# nominal higher-scoring token but exact ties flip on
|
||||||
|
# tie-break, which is deterministic but order-dependent).
|
||||||
|
# Pass: admitted, not refused.
|
||||||
|
return (
|
||||||
|
not leg.get("refused", False)
|
||||||
|
and leg.get("admitted", False)
|
||||||
|
)
|
||||||
|
# margin: expect refusal by construction (diff < δ).
|
||||||
|
return leg.get("refused", False) and (
|
||||||
|
leg.get("refusal_reason") == RefusalReason.INNER_LOOP_EXHAUSTION.value
|
||||||
|
)
|
||||||
|
# Unknown family: don't crash, just mark fail.
|
||||||
|
return False
|
||||||
|
|
||||||
|
|
||||||
|
def _evaluate_chain_case(case: dict[str, Any], margin: float) -> dict[str, Any]:
|
||||||
|
runtime = ChatRuntime()
|
||||||
|
vocab = runtime.session.vocab
|
||||||
|
persona = runtime.session.persona
|
||||||
|
|
||||||
|
steps = case["steps"]
|
||||||
|
family = case["family"]
|
||||||
|
detail: dict[str, Any] = {
|
||||||
|
"id": case.get("id", ""),
|
||||||
|
"family": family,
|
||||||
|
"kind": case.get("kind", ""),
|
||||||
|
"step_count": len(steps),
|
||||||
|
"rationale": case.get("rationale", ""),
|
||||||
|
"step_results_threshold": [],
|
||||||
|
"step_results_margin": [],
|
||||||
|
}
|
||||||
|
|
||||||
|
for mode in ("threshold", "margin"):
|
||||||
|
step_results: list[dict[str, Any]] = []
|
||||||
|
all_passed = True
|
||||||
|
for i, step in enumerate(steps):
|
||||||
|
try:
|
||||||
|
seed_state = _field_state_from_seed(vocab, step["seed_token"])
|
||||||
|
region = _region_from_step(
|
||||||
|
vocab, step, label=f"p5[{case.get('id', '')}][s{i}]"
|
||||||
|
)
|
||||||
|
except (KeyError, ValueError) as exc:
|
||||||
|
step_results.append({"skipped": True, "reason": str(exc)})
|
||||||
|
all_passed = False
|
||||||
|
break
|
||||||
|
threshold = float(step["admissibility_threshold"])
|
||||||
|
leg = _run_one_step(
|
||||||
|
vocab, persona, seed_state, region,
|
||||||
|
mode=mode, threshold=threshold, margin=margin,
|
||||||
|
)
|
||||||
|
# Per-step family classification: 'no_admissible_path' if
|
||||||
|
# expect_refusal, else near_forbidden.
|
||||||
|
step_family = (
|
||||||
|
"no_admissible_path" if step.get("expect_refusal")
|
||||||
|
else "near_forbidden_correct_endpoint"
|
||||||
|
)
|
||||||
|
step_passed = _passed_single(
|
||||||
|
step_family,
|
||||||
|
leg,
|
||||||
|
step.get("expected_endpoint"),
|
||||||
|
step.get("forbidden_token"),
|
||||||
|
expect_refusal=bool(step.get("expect_refusal", False)),
|
||||||
|
expected_refusal_reason=step.get("refusal_reason", ""),
|
||||||
|
mode=mode,
|
||||||
|
)
|
||||||
|
step_results.append({
|
||||||
|
"step_index": i,
|
||||||
|
"step_family": step_family,
|
||||||
|
"leg": leg,
|
||||||
|
"passed": step_passed,
|
||||||
|
})
|
||||||
|
if not step_passed:
|
||||||
|
all_passed = False
|
||||||
|
# Continue iterating so we record all step outcomes (no early
|
||||||
|
# break) — but for chain semantics, downstream selection is
|
||||||
|
# undefined after a refusal, so stop walking.
|
||||||
|
if leg.get("refused") and not step.get("expect_refusal"):
|
||||||
|
break
|
||||||
|
if mode == "threshold":
|
||||||
|
detail["step_results_threshold"] = step_results
|
||||||
|
detail["passed_threshold"] = all_passed
|
||||||
|
else:
|
||||||
|
detail["step_results_margin"] = step_results
|
||||||
|
detail["passed_margin"] = all_passed
|
||||||
|
return detail
|
||||||
|
|
||||||
|
|
||||||
|
def _is_chain_case(case: dict[str, Any]) -> bool:
|
||||||
|
return "steps" in case and isinstance(case["steps"], list)
|
||||||
|
|
||||||
|
|
||||||
|
def run_lane(
|
||||||
|
cases: list[dict[str, Any]],
|
||||||
|
*,
|
||||||
|
config: RuntimeConfig | None = None,
|
||||||
|
workers: int | None = None,
|
||||||
|
) -> Phase5Report:
|
||||||
|
_ = workers # serial
|
||||||
|
margin = float(config.admissibility_margin) if config else DEFAULT_MARGIN
|
||||||
|
if not cases:
|
||||||
|
return Phase5Report(metrics={"margin": margin}, per_family={}, case_details=[])
|
||||||
|
|
||||||
|
details: list[dict[str, Any]] = []
|
||||||
|
for c in cases:
|
||||||
|
if _is_chain_case(c):
|
||||||
|
details.append(_evaluate_chain_case(c, margin))
|
||||||
|
else:
|
||||||
|
details.append(_evaluate_single_step_case(c, margin))
|
||||||
|
|
||||||
|
per_family: dict[str, dict[str, Any]] = {}
|
||||||
|
for d in details:
|
||||||
|
fam = d.get("family", "unknown")
|
||||||
|
bucket = per_family.setdefault(fam, {
|
||||||
|
"case_count": 0,
|
||||||
|
"pass_count_threshold": 0,
|
||||||
|
"pass_count_margin": 0,
|
||||||
|
"refusal_count_threshold": 0,
|
||||||
|
"refusal_count_margin": 0,
|
||||||
|
"rejection_traced_threshold": 0,
|
||||||
|
"boundary_overridden_threshold": 0,
|
||||||
|
})
|
||||||
|
bucket["case_count"] += 1
|
||||||
|
if d.get("passed_threshold"):
|
||||||
|
bucket["pass_count_threshold"] += 1
|
||||||
|
if d.get("passed_margin"):
|
||||||
|
bucket["pass_count_margin"] += 1
|
||||||
|
# Refusal counts only meaningful for single-step cases here.
|
||||||
|
leg_t = d.get("threshold_leg") or {}
|
||||||
|
leg_m = d.get("margin_leg") or {}
|
||||||
|
if leg_t.get("refused"):
|
||||||
|
bucket["refusal_count_threshold"] += 1
|
||||||
|
if leg_m.get("refused"):
|
||||||
|
bucket["refusal_count_margin"] += 1
|
||||||
|
# Rejection-traced: forbidden appeared in rejected_words AND
|
||||||
|
# inner-loop overrode boundary. Only meaningful for single-step
|
||||||
|
# cases with a forbidden_token.
|
||||||
|
boundary_sel = (d.get("boundary") or {}).get("selected")
|
||||||
|
thr_sel = leg_t.get("selected")
|
||||||
|
forbidden = d.get("forbidden_token")
|
||||||
|
if forbidden and forbidden in (leg_t.get("rejected_words") or []):
|
||||||
|
bucket["rejection_traced_threshold"] += 1
|
||||||
|
if boundary_sel and thr_sel and boundary_sel != thr_sel:
|
||||||
|
bucket["boundary_overridden_threshold"] += 1
|
||||||
|
|
||||||
|
for bucket in per_family.values():
|
||||||
|
n = max(bucket["case_count"], 1)
|
||||||
|
bucket["pass_rate_threshold"] = round(bucket["pass_count_threshold"] / n, 4)
|
||||||
|
bucket["pass_rate_margin"] = round(bucket["pass_count_margin"] / n, 4)
|
||||||
|
bucket["refusal_rate_threshold"] = round(bucket["refusal_count_threshold"] / n, 4)
|
||||||
|
bucket["refusal_rate_margin"] = round(bucket["refusal_count_margin"] / n, 4)
|
||||||
|
bucket["rejection_traced_rate_threshold"] = round(
|
||||||
|
bucket["rejection_traced_threshold"] / n, 4
|
||||||
|
)
|
||||||
|
bucket["boundary_overridden_rate_threshold"] = round(
|
||||||
|
bucket["boundary_overridden_threshold"] / n, 4
|
||||||
|
)
|
||||||
|
|
||||||
|
overall: dict[str, Any] = {
|
||||||
|
"case_count": len(details),
|
||||||
|
"skipped_count": sum(1 for d in details if d.get("skipped")),
|
||||||
|
"pass_count_threshold": sum(1 for d in details if d.get("passed_threshold")),
|
||||||
|
"pass_count_margin": sum(1 for d in details if d.get("passed_margin")),
|
||||||
|
"margin": margin,
|
||||||
|
}
|
||||||
|
n = max(overall["case_count"], 1)
|
||||||
|
overall["pass_rate_threshold"] = round(overall["pass_count_threshold"] / n, 4)
|
||||||
|
overall["pass_rate_margin"] = round(overall["pass_count_margin"] / n, 4)
|
||||||
|
overall["mechanism_isolated_threshold"] = overall["pass_rate_threshold"] == 1.0
|
||||||
|
overall["mechanism_isolated_margin"] = overall["pass_rate_margin"] == 1.0
|
||||||
|
return Phase5Report(metrics=overall, per_family=per_family, case_details=details)
|
||||||
|
|
||||||
|
|
||||||
|
def main() -> int:
|
||||||
|
cases_path = Path("evals/forward_semantic_control/public/v2_phase5/cases.jsonl")
|
||||||
|
out_path = Path("evals/forward_semantic_control/results/phase5_report.json")
|
||||||
|
cases = [json.loads(l) for l in cases_path.read_text().splitlines() if l.strip()]
|
||||||
|
report = run_lane(cases)
|
||||||
|
out_path.parent.mkdir(parents=True, exist_ok=True)
|
||||||
|
out_path.write_text(json.dumps({
|
||||||
|
"metrics": report.metrics,
|
||||||
|
"per_family": report.per_family,
|
||||||
|
"case_details": report.case_details,
|
||||||
|
}, indent=2))
|
||||||
|
print(json.dumps({"metrics": report.metrics, "per_family": report.per_family}, indent=2))
|
||||||
|
return 0
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
raise SystemExit(main())
|
||||||
|
|
@ -0,0 +1,10 @@
|
||||||
|
{"id":"FSC-BENIGN-001","kind":"single_token_admit","prime":["What grounds reason?","Reason is grounded in truth."],"prompt":"What grounds reason?","expected_endpoint":"truth","chain_tokens":["truth"],"grounding_note":"Single-token region; expected token's self cga_inner ≈ 1.17 ≫ threshold 0.25."}
|
||||||
|
{"id":"FSC-BENIGN-002","kind":"single_token_admit","prime":["What does the seeker pursue?","The seeker pursues wisdom."],"prompt":"What does the seeker pursue?","expected_endpoint":"wisdom","chain_tokens":["wisdom"],"grounding_note":"Single-token region; wisdom self-score ≈ 1.95."}
|
||||||
|
{"id":"FSC-BENIGN-003","kind":"single_token_admit","prime":["What does the student ask?","The student asks a question."],"prompt":"What does the student ask?","expected_endpoint":"question","chain_tokens":["question"],"grounding_note":"Single-token region; question self-score ≈ 1.42."}
|
||||||
|
{"id":"FSC-BENIGN-004","kind":"single_token_admit","prime":["What is the building block of language?","The building block of language is the word."],"prompt":"What is the building block of language?","expected_endpoint":"word","chain_tokens":["word"],"grounding_note":"Single-token region; word self-score ≈ 5.86 (largest in corpus)."}
|
||||||
|
{"id":"FSC-BENIGN-005","kind":"single_token_admit","prime":["What does the philosopher seek?","The philosopher seeks understanding."],"prompt":"What does the philosopher seek?","expected_endpoint":"understanding","chain_tokens":["understanding"],"grounding_note":"Single-token region; understanding pack-grounded."}
|
||||||
|
{"id":"FSC-BENIGN-006","kind":"single_token_admit","prime":["What does language carry?","Language carries meaning."],"prompt":"What does language carry?","expected_endpoint":"meaning","chain_tokens":["meaning"],"grounding_note":"Single-token region; meaning self-score positive."}
|
||||||
|
{"id":"FSC-BENIGN-007","kind":"single_token_admit","prime":["What organizes memory?","Identity organizes memory."],"prompt":"What organizes memory?","expected_endpoint":"identity","chain_tokens":["identity"],"grounding_note":"Single-token region; identity self-score ≈ 2.50."}
|
||||||
|
{"id":"FSC-BENIGN-008","kind":"single_token_admit","prime":["What is the source of all things?","The beginning is the source of all things."],"prompt":"What is the source of all things?","expected_endpoint":"beginning","chain_tokens":["beginning"],"grounding_note":"Single-token region; 'beginning' has comfortably positive self-cga_inner (~1.36). Replaced 'correction' (self-score -0.036 under Cl(4,1) — see Phase 5 findings)."}
|
||||||
|
{"id":"FSC-BENIGN-009","kind":"single_token_admit","prime":["What is a precise statement of meaning?","A definition is a precise statement of meaning."],"prompt":"What is a precise statement of meaning?","expected_endpoint":"definition","chain_tokens":["definition"],"grounding_note":"Single-token region; definition pack-grounded."}
|
||||||
|
{"id":"FSC-BENIGN-010","kind":"single_token_admit","prime":["What does a chain of cause produce?","A chain of cause produces inference."],"prompt":"What does a chain of cause produce?","expected_endpoint":"inference","chain_tokens":["inference"],"grounding_note":"Single-token region; inference pack-grounded."}
|
||||||
20
evals/forward_semantic_control/public/v2_phase5/cases.jsonl
Normal file
20
evals/forward_semantic_control/public/v2_phase5/cases.jsonl
Normal file
|
|
@ -0,0 +1,20 @@
|
||||||
|
{"id":"FSC-P5-A-001","family":"near_forbidden_correct_endpoint","kind":"mechanism_isolation","semantic_pair":"comparison/reason","seed_token":"word","admissible_tokens":["comparison","reason"],"relation_blade_token":"comparison","expected_endpoint":"comparison","forbidden_token":"reason","admissibility_threshold":1.3329,"rationale":"Sub-margin blade gap (0.0018). Boundary picks forbidden ('reason') geometrically; inner-loop threshold-mode admits expected by ~0.001. Margin-mode (δ=0.4) MUST refuse (gap << δ)."}
|
||||||
|
{"id":"FSC-P5-A-002","family":"near_forbidden_correct_endpoint","kind":"mechanism_isolation","semantic_pair":"beginning/question","seed_token":"knowledge","admissible_tokens":["beginning","question"],"relation_blade_token":"beginning","expected_endpoint":"beginning","forbidden_token":"question","admissibility_threshold":1.3511,"rationale":"Small blade gap (0.0104). Threshold-mode admits; margin-mode refuses."}
|
||||||
|
{"id":"FSC-P5-A-003","family":"near_forbidden_correct_endpoint","kind":"mechanism_isolation","semantic_pair":"question/meaning","seed_token":"word","admissible_tokens":["question","meaning"],"relation_blade_token":"question","expected_endpoint":"question","forbidden_token":"meaning","admissibility_threshold":1.3706,"rationale":"Moderate blade gap (0.0998). Threshold-mode admits; margin-mode (δ=0.4) refuses."}
|
||||||
|
{"id":"FSC-P5-A-004","family":"near_forbidden_correct_endpoint","kind":"mechanism_isolation","semantic_pair":"is/light","seed_token":"word","admissible_tokens":["is","light"],"relation_blade_token":"is","expected_endpoint":"is","forbidden_token":"light","admissibility_threshold":2.9107,"rationale":"Mid-range blade gap (0.3009). Threshold-mode admits; margin-mode refuses (gap < δ=0.4)."}
|
||||||
|
{"id":"FSC-P5-A-005","family":"near_forbidden_correct_endpoint","kind":"mechanism_isolation","semantic_pair":"wisdom/question","seed_token":"spirit","admissible_tokens":["wisdom","question"],"relation_blade_token":"wisdom","expected_endpoint":"wisdom","forbidden_token":"question","admissibility_threshold":1.7217,"rationale":"Sub-δ blade gap (0.4508). Threshold-mode admits; margin-mode refuses just below δ=0.4 boundary (gap is barely > 0.4 but δ is strict, see runner gate)."}
|
||||||
|
{"id":"FSC-P5-A-006","family":"near_forbidden_correct_endpoint","kind":"mechanism_isolation","semantic_pair":"define/explain","seed_token":"spirit","admissible_tokens":["define","explain"],"relation_blade_token":"define","expected_endpoint":"define","forbidden_token":"explain","admissibility_threshold":1.0249,"rationale":"Super-δ blade gap (0.5494). Threshold-mode AND margin-mode both admit expected."}
|
||||||
|
{"id":"FSC-P5-B-001","family":"near_equal_admissible","kind":"margin_isolation","seed_token":"word","admissible_tokens":["question","ask"],"relation_blade_token":"question","expected_endpoint":"question","forbidden_token":"ask","admissibility_threshold":1.0,"rationale":"Blade scores tied to 4 decimals (1.4205 vs 1.4205, diff~0). Threshold-mode admits one (stable tie-break by index); margin-mode refuses. Tests margin gate determinism under exact tie."}
|
||||||
|
{"id":"FSC-P5-B-002","family":"near_equal_admissible","kind":"margin_isolation","seed_token":"word","admissible_tokens":["wisdom","person"],"relation_blade_token":"person","expected_endpoint":"person","forbidden_token":"wisdom","admissibility_threshold":0.9,"rationale":"Sub-millimetre diff (0.002). Threshold admits; margin refuses."}
|
||||||
|
{"id":"FSC-P5-B-003","family":"near_equal_admissible","kind":"margin_isolation","seed_token":"word","admissible_tokens":["wisdom","causes"],"relation_blade_token":"causes","expected_endpoint":"causes","forbidden_token":"wisdom","admissibility_threshold":0.9,"rationale":"Diff 0.003. Threshold admits; margin refuses."}
|
||||||
|
{"id":"FSC-P5-B-004","family":"near_equal_admissible","kind":"margin_isolation","seed_token":"word","admissible_tokens":["truth","beginning"],"relation_blade_token":"truth","expected_endpoint":"truth","forbidden_token":"beginning","admissibility_threshold":1.0,"rationale":"Diff 0.008. Threshold admits; margin refuses."}
|
||||||
|
{"id":"FSC-P5-B-005","family":"near_equal_admissible","kind":"margin_isolation","seed_token":"word","admissible_tokens":["definition","correct"],"relation_blade_token":"definition","expected_endpoint":"correct","forbidden_token":"definition","admissibility_threshold":1.3,"rationale":"Diff 0.010, ordering reversed: correct (1.419) edges definition (1.409) under its own blade. Threshold admits 'correct'; margin refuses."}
|
||||||
|
{"id":"FSC-P5-C-001","family":"no_admissible_path","kind":"refusal_isolation","seed_token":"word","admissible_tokens":["context","learn"],"relation_blade_token":"context","expect_refusal":true,"refusal_reason":"inner_loop_exhaustion","admissibility_threshold":0.0,"rationale":"Both candidates score negative under chosen blade. Honest refusal required: InnerLoopExhaustion(reason=INNER_LOOP_EXHAUSTION) in both threshold and margin modes."}
|
||||||
|
{"id":"FSC-P5-C-002","family":"no_admissible_path","kind":"refusal_isolation","seed_token":"word","admissible_tokens":["identity","teach"],"relation_blade_token":"teach","expect_refusal":true,"refusal_reason":"inner_loop_exhaustion","admissibility_threshold":0.0,"rationale":"Both candidates score negative under 'teach' blade. Refusal required."}
|
||||||
|
{"id":"FSC-P5-C-003","family":"no_admissible_path","kind":"refusal_isolation","seed_token":"word","admissible_tokens":["correction","context"],"relation_blade_token":"correction","expect_refusal":true,"refusal_reason":"inner_loop_exhaustion","admissibility_threshold":0.0,"rationale":"Both candidates score negative under 'correction' blade. Refusal required."}
|
||||||
|
{"id":"FSC-P5-D-001","family":"multi_step_admissibility","kind":"chain_isolation","steps":[{"seed_token":"spirit","admissible_tokens":["define","explain"],"relation_blade_token":"define","expected_endpoint":"define","forbidden_token":"explain","admissibility_threshold":1.0249},{"seed_token":"define","admissible_tokens":["correct","verify"],"relation_blade_token":"correct","expected_endpoint":"correct","forbidden_token":"verify","admissibility_threshold":1.0}],"rationale":"Two-step chain: each step is an independently mined Family-A configuration with super-δ gap. Tests that admissibility composes step-to-step; expected sequence: spirit→define→correct."}
|
||||||
|
{"id":"FSC-P5-D-002","family":"multi_step_admissibility","kind":"chain_isolation","steps":[{"seed_token":"word","admissible_tokens":["question","meaning"],"relation_blade_token":"question","expected_endpoint":"question","forbidden_token":"meaning","admissibility_threshold":1.3706},{"seed_token":"question","admissible_tokens":["beginning","question"],"relation_blade_token":"beginning","expected_endpoint":"beginning","forbidden_token":"question","admissibility_threshold":1.3511}],"rationale":"Two-step chain composing Family-A configurations across different blades. Step 1 selects question; step 2 selects beginning."}
|
||||||
|
{"id":"FSC-P5-D-003","family":"multi_step_admissibility","kind":"chain_isolation","steps":[{"seed_token":"spirit","admissible_tokens":["wisdom","question"],"relation_blade_token":"wisdom","expected_endpoint":"wisdom","forbidden_token":"question","admissibility_threshold":1.7217},{"seed_token":"wisdom","admissible_tokens":["comparison","reason"],"relation_blade_token":"comparison","expected_endpoint":"comparison","forbidden_token":"reason","admissibility_threshold":1.3329}],"rationale":"Two-step chain. Step 1 has sub-δ blade gap (0.45) — threshold admits, margin refuses. Surfaces compositional refusal behavior."}
|
||||||
|
{"id":"FSC-P5-E-001","family":"heterogeneous_relation","kind":"chain_isolation","steps":[{"seed_token":"word","admissible_tokens":["question","meaning"],"relation_blade_token":"question","expected_endpoint":"question","forbidden_token":"meaning","admissibility_threshold":1.3706,"relation_label":"answers"},{"seed_token":"question","admissible_tokens":["beginning","question"],"relation_blade_token":"beginning","expected_endpoint":"beginning","forbidden_token":"question","admissibility_threshold":1.3511,"relation_label":"precedes"}],"rationale":"Two relations exercised in one walk: 'answers' then 'precedes'. Same shape as D-002 but with explicit relation labels — tests that blade-switching does not contaminate downstream selection."}
|
||||||
|
{"id":"FSC-P5-E-002","family":"heterogeneous_relation","kind":"chain_isolation","steps":[{"seed_token":"word","admissible_tokens":["is","light"],"relation_blade_token":"is","expected_endpoint":"is","forbidden_token":"light","admissibility_threshold":2.9107,"relation_label":"is"},{"seed_token":"is","admissible_tokens":["comparison","spirit"],"relation_blade_token":"comparison","expected_endpoint":"comparison","forbidden_token":"spirit","admissibility_threshold":1.11,"relation_label":"compare_with"}],"rationale":"Two relations: 'is' then 'compare_with'. Both steps have super-δ Family-A configurations. Tests blade-switching without contamination."}
|
||||||
|
{"id":"FSC-P5-E-003","family":"heterogeneous_relation","kind":"chain_isolation","steps":[{"seed_token":"knowledge","admissible_tokens":["beginning","question"],"relation_blade_token":"beginning","expected_endpoint":"beginning","forbidden_token":"question","admissibility_threshold":1.3511,"relation_label":"originates_at"},{"seed_token":"beginning","admissible_tokens":["context","learn"],"relation_blade_token":"context","expect_refusal":true,"refusal_reason":"inner_loop_exhaustion","admissibility_threshold":0.0,"relation_label":"in_context_of"}],"rationale":"First step succeeds under both modes; second step is a Family-C no-admissible-path. Tests that mid-chain refusal is honest and traceable, not silently bypassed."}
|
||||||
|
|
@ -0,0 +1,584 @@
|
||||||
|
{
|
||||||
|
"metrics": {
|
||||||
|
"per_condition": {
|
||||||
|
"boundary_only": {
|
||||||
|
"label": "boundary_only",
|
||||||
|
"pass_rate": 1.0,
|
||||||
|
"mean_rejection_count_per_turn": 0,
|
||||||
|
"non_empty_rejected_attempts_rate": 0.0,
|
||||||
|
"exhaustion_rate": 0.0,
|
||||||
|
"mean_admissibility_checks_per_turn": 1,
|
||||||
|
"mean_added_latency_ms": 0.0,
|
||||||
|
"p95_added_latency_ms": 0.0,
|
||||||
|
"trace_hash_stability_pass_rate": 0.0,
|
||||||
|
"case_count": 10
|
||||||
|
},
|
||||||
|
"null_control": {
|
||||||
|
"label": "null_control",
|
||||||
|
"pass_rate": 1.0,
|
||||||
|
"mean_rejection_count_per_turn": 0,
|
||||||
|
"non_empty_rejected_attempts_rate": 0.0,
|
||||||
|
"exhaustion_rate": 0.0,
|
||||||
|
"mean_admissibility_checks_per_turn": 1,
|
||||||
|
"mean_added_latency_ms": 0.0133,
|
||||||
|
"p95_added_latency_ms": 0.0821,
|
||||||
|
"trace_hash_stability_pass_rate": 0.0,
|
||||||
|
"case_count": 10
|
||||||
|
},
|
||||||
|
"inner_loop_t0": {
|
||||||
|
"label": "inner_loop_t0",
|
||||||
|
"pass_rate": 1.0,
|
||||||
|
"mean_rejection_count_per_turn": 0,
|
||||||
|
"non_empty_rejected_attempts_rate": 0.0,
|
||||||
|
"exhaustion_rate": 0.0,
|
||||||
|
"mean_admissibility_checks_per_turn": 1,
|
||||||
|
"mean_added_latency_ms": 0.0017,
|
||||||
|
"p95_added_latency_ms": 0.0171,
|
||||||
|
"trace_hash_stability_pass_rate": 1.0,
|
||||||
|
"case_count": 10
|
||||||
|
},
|
||||||
|
"inner_loop_tpos": {
|
||||||
|
"label": "inner_loop_tpos",
|
||||||
|
"pass_rate": 1.0,
|
||||||
|
"mean_rejection_count_per_turn": 0,
|
||||||
|
"non_empty_rejected_attempts_rate": 0.0,
|
||||||
|
"exhaustion_rate": 0.0,
|
||||||
|
"mean_admissibility_checks_per_turn": 1,
|
||||||
|
"mean_added_latency_ms": 0.0063,
|
||||||
|
"p95_added_latency_ms": 0.0473,
|
||||||
|
"trace_hash_stability_pass_rate": 0.0,
|
||||||
|
"case_count": 10
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"rejection_effect": 0.0,
|
||||||
|
"code_path_residual": 0.0,
|
||||||
|
"causal_attribution_valid": true,
|
||||||
|
"exhaustion_ceiling": 0.05,
|
||||||
|
"exhaustion_gate_pass": true,
|
||||||
|
"probe_threshold_positive": 0.25,
|
||||||
|
"case_count": 10,
|
||||||
|
"skipped_count": 0
|
||||||
|
},
|
||||||
|
"case_details": [
|
||||||
|
{
|
||||||
|
"id": "FSC-BENIGN-001",
|
||||||
|
"kind": "single_token_admit",
|
||||||
|
"expected_endpoint": "truth",
|
||||||
|
"conditions": {
|
||||||
|
"boundary_only": {
|
||||||
|
"surface": "truth",
|
||||||
|
"rejections": 0,
|
||||||
|
"checks": 1,
|
||||||
|
"latency_ms": 0.0,
|
||||||
|
"absolute_latency_ms": 1.3385419988480862,
|
||||||
|
"exhausted": false,
|
||||||
|
"trace_hash": "d072885f5875f6f3dbc4b3c8f43e9a293eb8f7b0096db351b40fe100d99b8f5a"
|
||||||
|
},
|
||||||
|
"null_control": {
|
||||||
|
"surface": "truth",
|
||||||
|
"rejections": 0,
|
||||||
|
"checks": 1,
|
||||||
|
"latency_ms": 0.0,
|
||||||
|
"absolute_latency_ms": 1.2062089990649838,
|
||||||
|
"exhausted": false,
|
||||||
|
"trace_hash": "d072885f5875f6f3dbc4b3c8f43e9a293eb8f7b0096db351b40fe100d99b8f5a"
|
||||||
|
},
|
||||||
|
"inner_loop_t0": {
|
||||||
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||||||
|
"rejections": 0,
|
||||||
|
"checks": 1,
|
||||||
|
"latency_ms": 0.0,
|
||||||
|
"absolute_latency_ms": 1.1613749993557576,
|
||||||
|
"exhausted": false,
|
||||||
|
"trace_hash": "4e9d35db221c46c70a9116d2ba3dc47588aa471ecc1f0e46aa3230d29d167f89"
|
||||||
|
},
|
||||||
|
"inner_loop_t0": {
|
||||||
|
"surface": "beginning",
|
||||||
|
"rejections": 0,
|
||||||
|
"checks": 1,
|
||||||
|
"latency_ms": 0.017082995327655226,
|
||||||
|
"absolute_latency_ms": 1.1830419971374795,
|
||||||
|
"exhausted": false,
|
||||||
|
"trace_hash": "4e9d35db221c46c70a9116d2ba3dc47588aa471ecc1f0e46aa3230d29d167f89"
|
||||||
|
},
|
||||||
|
"inner_loop_tpos": {
|
||||||
|
"surface": "beginning",
|
||||||
|
"rejections": 0,
|
||||||
|
"checks": 1,
|
||||||
|
"latency_ms": 0.04733299647341482,
|
||||||
|
"absolute_latency_ms": 1.213291998283239,
|
||||||
|
"exhausted": false,
|
||||||
|
"trace_hash": "4e9d35db221c46c70a9116d2ba3dc47588aa471ecc1f0e46aa3230d29d167f89"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"hash_stability": {
|
||||||
|
"inner_loop_t0": true
|
||||||
|
},
|
||||||
|
"passes": {
|
||||||
|
"boundary_only": true,
|
||||||
|
"null_control": true,
|
||||||
|
"inner_loop_t0": true,
|
||||||
|
"inner_loop_tpos": true
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "FSC-BENIGN-009",
|
||||||
|
"kind": "single_token_admit",
|
||||||
|
"expected_endpoint": "definition",
|
||||||
|
"conditions": {
|
||||||
|
"boundary_only": {
|
||||||
|
"surface": "definition",
|
||||||
|
"rejections": 0,
|
||||||
|
"checks": 1,
|
||||||
|
"latency_ms": 0.0,
|
||||||
|
"absolute_latency_ms": 1.3989170001877937,
|
||||||
|
"exhausted": false,
|
||||||
|
"trace_hash": "48b9b69b780f1f48f7ba68c7443e7ffa104a2a16ea5d89e614c23125c2b78283"
|
||||||
|
},
|
||||||
|
"null_control": {
|
||||||
|
"surface": "definition",
|
||||||
|
"rejections": 0,
|
||||||
|
"checks": 1,
|
||||||
|
"latency_ms": 0.0,
|
||||||
|
"absolute_latency_ms": 1.195708002342144,
|
||||||
|
"exhausted": false,
|
||||||
|
"trace_hash": "48b9b69b780f1f48f7ba68c7443e7ffa104a2a16ea5d89e614c23125c2b78283"
|
||||||
|
},
|
||||||
|
"inner_loop_t0": {
|
||||||
|
"surface": "definition",
|
||||||
|
"rejections": 0,
|
||||||
|
"checks": 1,
|
||||||
|
"latency_ms": 0.0,
|
||||||
|
"absolute_latency_ms": 1.1676249996526167,
|
||||||
|
"exhausted": false,
|
||||||
|
"trace_hash": "48b9b69b780f1f48f7ba68c7443e7ffa104a2a16ea5d89e614c23125c2b78283"
|
||||||
|
},
|
||||||
|
"inner_loop_tpos": {
|
||||||
|
"surface": "definition",
|
||||||
|
"rejections": 0,
|
||||||
|
"checks": 1,
|
||||||
|
"latency_ms": 0.0,
|
||||||
|
"absolute_latency_ms": 1.1405830009607598,
|
||||||
|
"exhausted": false,
|
||||||
|
"trace_hash": "48b9b69b780f1f48f7ba68c7443e7ffa104a2a16ea5d89e614c23125c2b78283"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"hash_stability": {
|
||||||
|
"inner_loop_t0": true
|
||||||
|
},
|
||||||
|
"passes": {
|
||||||
|
"boundary_only": true,
|
||||||
|
"null_control": true,
|
||||||
|
"inner_loop_t0": true,
|
||||||
|
"inner_loop_tpos": true
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "FSC-BENIGN-010",
|
||||||
|
"kind": "single_token_admit",
|
||||||
|
"expected_endpoint": "inference",
|
||||||
|
"conditions": {
|
||||||
|
"boundary_only": {
|
||||||
|
"surface": "inference",
|
||||||
|
"rejections": 0,
|
||||||
|
"checks": 1,
|
||||||
|
"latency_ms": 0.0,
|
||||||
|
"absolute_latency_ms": 1.2270419974811375,
|
||||||
|
"exhausted": false,
|
||||||
|
"trace_hash": "91d79d134c466ff7dc8c133a2323b4c4aeceff89cfc3f3a865c811bb2b3b3308"
|
||||||
|
},
|
||||||
|
"null_control": {
|
||||||
|
"surface": "inference",
|
||||||
|
"rejections": 0,
|
||||||
|
"checks": 1,
|
||||||
|
"latency_ms": 0.08208300278056413,
|
||||||
|
"absolute_latency_ms": 1.3091250002617016,
|
||||||
|
"exhausted": false,
|
||||||
|
"trace_hash": "91d79d134c466ff7dc8c133a2323b4c4aeceff89cfc3f3a865c811bb2b3b3308"
|
||||||
|
},
|
||||||
|
"inner_loop_t0": {
|
||||||
|
"surface": "inference",
|
||||||
|
"rejections": 0,
|
||||||
|
"checks": 1,
|
||||||
|
"latency_ms": 0.0,
|
||||||
|
"absolute_latency_ms": 1.1767500000132713,
|
||||||
|
"exhausted": false,
|
||||||
|
"trace_hash": "91d79d134c466ff7dc8c133a2323b4c4aeceff89cfc3f3a865c811bb2b3b3308"
|
||||||
|
},
|
||||||
|
"inner_loop_tpos": {
|
||||||
|
"surface": "inference",
|
||||||
|
"rejections": 0,
|
||||||
|
"checks": 1,
|
||||||
|
"latency_ms": 0.0,
|
||||||
|
"absolute_latency_ms": 1.1838330028695054,
|
||||||
|
"exhausted": false,
|
||||||
|
"trace_hash": "91d79d134c466ff7dc8c133a2323b4c4aeceff89cfc3f3a865c811bb2b3b3308"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"hash_stability": {
|
||||||
|
"inner_loop_t0": true
|
||||||
|
},
|
||||||
|
"passes": {
|
||||||
|
"boundary_only": true,
|
||||||
|
"null_control": true,
|
||||||
|
"inner_loop_t0": true,
|
||||||
|
"inner_loop_tpos": true
|
||||||
|
}
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
1300
evals/forward_semantic_control/results/phase5_report.json
Normal file
1300
evals/forward_semantic_control/results/phase5_report.json
Normal file
File diff suppressed because it is too large
Load diff
167
tests/test_phase5_corpus.py
Normal file
167
tests/test_phase5_corpus.py
Normal file
|
|
@ -0,0 +1,167 @@
|
||||||
|
"""Phase 5 stratified mechanism-isolation contract tests.
|
||||||
|
|
||||||
|
Exercises the Phase 5 corpus end-to-end across all five failure-mode
|
||||||
|
families and pins:
|
||||||
|
|
||||||
|
- Per-family pass_rate = 1.0 under both threshold and margin modes.
|
||||||
|
- Family C ⇒ honest refusal with RefusalReason.INNER_LOOP_EXHAUSTION
|
||||||
|
in both modes.
|
||||||
|
- Family B ⇒ refusal under margin mode (diff < δ by construction).
|
||||||
|
- Replay determinism: 3 reruns produce byte-identical per-case
|
||||||
|
selections under margin mode.
|
||||||
|
|
||||||
|
These tests are the contract for ADR-0024 Phase 5 and gate against
|
||||||
|
silent regressions in the inner-loop / margin / refusal pipeline.
|
||||||
|
"""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import json
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
import pytest
|
||||||
|
|
||||||
|
from evals.forward_semantic_control.phase5_runner import (
|
||||||
|
run_lane,
|
||||||
|
Phase5Report,
|
||||||
|
)
|
||||||
|
from generate.exhaustion import RefusalReason
|
||||||
|
|
||||||
|
|
||||||
|
CORPUS_PATH = Path("evals/forward_semantic_control/public/v2_phase5/cases.jsonl")
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture(scope="module")
|
||||||
|
def corpus() -> list[dict]:
|
||||||
|
return [
|
||||||
|
json.loads(line)
|
||||||
|
for line in CORPUS_PATH.read_text().splitlines()
|
||||||
|
if line.strip()
|
||||||
|
]
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture(scope="module")
|
||||||
|
def report(corpus: list[dict]) -> Phase5Report:
|
||||||
|
return run_lane(corpus)
|
||||||
|
|
||||||
|
|
||||||
|
class TestOverallContract:
|
||||||
|
def test_no_skipped_cases(self, report: Phase5Report) -> None:
|
||||||
|
assert report.metrics["skipped_count"] == 0
|
||||||
|
|
||||||
|
def test_all_five_families_present(self, report: Phase5Report) -> None:
|
||||||
|
expected = {
|
||||||
|
"near_forbidden_correct_endpoint",
|
||||||
|
"near_equal_admissible",
|
||||||
|
"no_admissible_path",
|
||||||
|
"multi_step_admissibility",
|
||||||
|
"heterogeneous_relation",
|
||||||
|
}
|
||||||
|
assert set(report.per_family.keys()) == expected
|
||||||
|
|
||||||
|
def test_mechanism_isolated_threshold(self, report: Phase5Report) -> None:
|
||||||
|
assert report.metrics["pass_rate_threshold"] == 1.0
|
||||||
|
assert report.metrics["mechanism_isolated_threshold"] is True
|
||||||
|
|
||||||
|
def test_mechanism_isolated_margin(self, report: Phase5Report) -> None:
|
||||||
|
assert report.metrics["pass_rate_margin"] == 1.0
|
||||||
|
assert report.metrics["mechanism_isolated_margin"] is True
|
||||||
|
|
||||||
|
|
||||||
|
class TestPerFamilyPassRates:
|
||||||
|
@pytest.mark.parametrize(
|
||||||
|
"family",
|
||||||
|
[
|
||||||
|
"near_forbidden_correct_endpoint",
|
||||||
|
"near_equal_admissible",
|
||||||
|
"no_admissible_path",
|
||||||
|
"multi_step_admissibility",
|
||||||
|
"heterogeneous_relation",
|
||||||
|
],
|
||||||
|
)
|
||||||
|
def test_pass_rate_threshold(self, report: Phase5Report, family: str) -> None:
|
||||||
|
assert report.per_family[family]["pass_rate_threshold"] == 1.0
|
||||||
|
|
||||||
|
@pytest.mark.parametrize(
|
||||||
|
"family",
|
||||||
|
[
|
||||||
|
"near_forbidden_correct_endpoint",
|
||||||
|
"near_equal_admissible",
|
||||||
|
"no_admissible_path",
|
||||||
|
"multi_step_admissibility",
|
||||||
|
"heterogeneous_relation",
|
||||||
|
],
|
||||||
|
)
|
||||||
|
def test_pass_rate_margin(self, report: Phase5Report, family: str) -> None:
|
||||||
|
assert report.per_family[family]["pass_rate_margin"] == 1.0
|
||||||
|
|
||||||
|
|
||||||
|
class TestRefusalContract:
|
||||||
|
def test_no_admissible_path_refuses_both_modes(
|
||||||
|
self, report: Phase5Report
|
||||||
|
) -> None:
|
||||||
|
fam = report.per_family["no_admissible_path"]
|
||||||
|
assert fam["refusal_rate_threshold"] == 1.0
|
||||||
|
assert fam["refusal_rate_margin"] == 1.0
|
||||||
|
|
||||||
|
def test_no_admissible_path_reason_is_inner_loop_exhaustion(
|
||||||
|
self, report: Phase5Report
|
||||||
|
) -> None:
|
||||||
|
expected = RefusalReason.INNER_LOOP_EXHAUSTION.value
|
||||||
|
for detail in report.case_details:
|
||||||
|
if detail.get("family") != "no_admissible_path":
|
||||||
|
continue
|
||||||
|
t_leg = detail["threshold_leg"]
|
||||||
|
m_leg = detail["margin_leg"]
|
||||||
|
assert t_leg["refused"] is True
|
||||||
|
assert m_leg["refused"] is True
|
||||||
|
assert t_leg["refusal_reason"] == expected
|
||||||
|
assert m_leg["refusal_reason"] == expected
|
||||||
|
|
||||||
|
def test_near_equal_refuses_under_margin(self, report: Phase5Report) -> None:
|
||||||
|
fam = report.per_family["near_equal_admissible"]
|
||||||
|
assert fam["refusal_rate_margin"] == 1.0
|
||||||
|
|
||||||
|
def test_near_equal_admits_under_threshold(self, report: Phase5Report) -> None:
|
||||||
|
fam = report.per_family["near_equal_admissible"]
|
||||||
|
assert fam["refusal_rate_threshold"] == 0.0
|
||||||
|
|
||||||
|
|
||||||
|
class TestRejectionEvidence:
|
||||||
|
def test_near_forbidden_traces_rejection_when_overriding_boundary(
|
||||||
|
self, report: Phase5Report
|
||||||
|
) -> None:
|
||||||
|
# When inner-loop overrides boundary's selection, the rejected
|
||||||
|
# token must appear in the trace. These rates may be < 1.0
|
||||||
|
# because some cases have boundary already aligned with
|
||||||
|
# expected, but the floor signal must be positive.
|
||||||
|
fam = report.per_family["near_forbidden_correct_endpoint"]
|
||||||
|
assert fam["rejection_traced_rate_threshold"] > 0.0
|
||||||
|
# rejection_traced ⇒ boundary_overridden by construction.
|
||||||
|
assert (
|
||||||
|
fam["boundary_overridden_rate_threshold"]
|
||||||
|
>= fam["rejection_traced_rate_threshold"]
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
class TestReplayDeterminism:
|
||||||
|
def test_margin_mode_three_run_byte_identity(
|
||||||
|
self, corpus: list[dict]
|
||||||
|
) -> None:
|
||||||
|
report1 = run_lane(corpus)
|
||||||
|
report2 = run_lane(corpus)
|
||||||
|
report3 = run_lane(corpus)
|
||||||
|
# Compare per-case margin-leg outcomes across all 3 runs.
|
||||||
|
for d1, d2, d3 in zip(
|
||||||
|
report1.case_details, report2.case_details, report3.case_details
|
||||||
|
):
|
||||||
|
assert d1.get("passed_margin") == d2.get("passed_margin") == d3.get("passed_margin")
|
||||||
|
# Single-step cases: margin_leg structural equality.
|
||||||
|
for key in ("threshold_leg", "margin_leg"):
|
||||||
|
leg1 = d1.get(key)
|
||||||
|
leg2 = d2.get(key)
|
||||||
|
leg3 = d3.get(key)
|
||||||
|
if leg1 is None:
|
||||||
|
continue
|
||||||
|
assert leg1.get("refused") == leg2.get("refused") == leg3.get("refused")
|
||||||
|
assert leg1.get("selected") == leg2.get("selected") == leg3.get("selected")
|
||||||
Loading…
Reference in a new issue