#000054 Phase 2: synonym_expand cap-aware + strict view + retrieval-route surfacing

End-to-end gap-close from the Phase 1 extractor. Five interlocking
fixes; live-verified that `what is a CPU?` → "Central processing unit"
at #1, `what is a GPU?` → "Graphics processing unit" at #1
EVIDENCE-WARRANTED 1/1; Mount Kilimanjaro / Soviet Union queries
unchanged (no regression).

(a) `synonym_expand` over-cap path is now rank-and-truncate by
source-frequency (descending) instead of hard-skip. CPU has 13
legitimate homonym expansions across the corpus; the prior
MAX_NEIGHBORS_PER_TOKEN=8 cap contributed *zero* expansion → no
canonical-article surfacing. Now: keep the 8 dominant by per-(token,
target) source-root count via _load_neighbor_source_freq.

(b) `_search_titles` orders by FTS5 bm25 ASC instead of LENGTH(title)
ASC on the FTS5-MATCH path. The length-asc tie-break was correct for
the 2026-05-02 "Back to the Future" LIKE-substring case but
counter-productive on FTS5 (tokenized; no substring junk; length-asc
preferred "Unit" / "Unite" / "B unit" over "Graphics processing
unit"). LIKE fallback keeps length-asc since the substring issue
persists there.

(c) `accept_tokens` (feeds title-search, core-keyword, title-rerank)
uses the synonym-expanded set instead of qtokens-only. The Phase 1
expansion existed but was only used in the FTS5 OR-fallback; satellite
articles saturated the budget before the canonical article entered.

(d) ARCHITECTURAL: `synonym_expand_strict()` (new — high-trust
evidence-kind subset: manual + manual_legacy + acronym_parens,
**excludes** link_reciprocity) for use in the multiplicative
`_rerank_by_title_purity` and as the source for `accept_tokens`.
Reciprocal-wikilink edges express *topical adjacency*, not synonymy
(a `Dinosaurs` page reciprocally links to `Curious George Brigade` →
edge that should not amplify retrieval); a multiplicative ranker over
them blows up. Strict view preserves the acronym-parens surfacing
(those edges ARE the phrase=expansion identity) while keeping
link-reciprocity to additive retrieval-route boosts via the broad
synonym_expand (still wired to `or_synonym_pool` for the FTS5 OR
fallback).

(e) Extractor regex tightened `[A-Z]{2,6}` → `[A-Z]{3,6}` and purged
~21K 2-letter acronym edges from shards. 2-letter acronyms (AI/ML/OS/
US/UK/IT/PC/TV) homonym-collide too often with common 2-letter QUERY
tokens like `go`/`is`/`am` — without this, "why did the dinosaurs go
extinct?" pulled Curious George Brigade via GO-acronym edges. The
high-value acronyms (CPU/GPU/RAM/DNA/FBI/WHO/…) all clear 3 chars.

Also: CLAUDE.md gains a "prefer existing ticket; only split for
Dav1d-review audience" discipline note (saved as feedback memory) —
this work is itself an example: would have been #000055 + #000056 +
#000057 under the prior pattern; instead extends #000054.

Suite: 2531 passed (no regression). bench-qa in flight separately.

docs/TICKETS.md

@@ -101,7 +101,7 @@ Newest first. Update on every open/close.
 
 | ID       | Title                                          | Status                | Opened     | Directive |
 |----------|------------------------------------------------|-----------------------|------------|-----------|
-| #000054  | Acronym-parens concept extractor (closes the abbreviation→expansion retrieval gap) | **closed · 2026-05-13** — `arborist/concepts/extract.py:acronym_parens_synonym` lands as a new corpus-agnostic extractor in `EXTRACTORS` (`evidence_kind="acronym_parens"`). Scans each doc's lead chunk for `<Multi-Word Phrase> (ACRO)` where the all-caps acronym's letters match the content-word initials of the phrase in order; emits bidirectional synonym edges between the lowercased acronym and each ≥3-char content token of the phrase. Conservative (strict 1:1 initials, function words filtered, repeated definitions deduped per doc). Closes the *retrieval-side* abbreviation gap (`CPU↔central processing unit`, `GPU↔graphics processing unit`, `RAM↔random access memory`, `FBI↔federal bureau of investigation`, `WHO↔world health organization`, …) that `link_reciprocity_synonym` can't reach because the relation lives in body text, not the wiki link graph (Wikipedia represents abbreviation→expansion as a *redirect* — not an edge). Per-shard like all `concept_relations` data; corpus-agnostic so HTML/blogs/textbooks benefit equally. Retrieval-side only — never proof-path. 8 new tests; full suite green. Closes #000050 §2a's CPU/GPU fixture rows *upstream* of vec; the Orwell-shape conceptual-allusion row remains the genuine #000050 justification. Operational follow-up (not code): `arborist concepts derive --extractor acronym_parens` on each shard. | 2026-05-13 | —         |
+| #000054  | Acronym-parens concept extractor (closes the abbreviation→expansion retrieval gap) | **in progress** — Phase 1 (extractor + 481K edges) landed `58027e9`; Phase 2 (consumer-side surfacing — `synonym_expand` rank-and-truncate over the per-token cap, FTS5-`bm25` ordering in `_search_titles`, expanded `accept_tokens` in title-search + core-keyword + title-rerank, `synonym_expand_strict()` for the multiplicative title-purity rerank to exclude noisy `link_reciprocity` edges, tightened extractor regex to `[A-Z]{3,6}` purging 2-letter homonym edges) pending commit. **End-to-end verified:** `what is a CPU?` → Central processing unit at #1; `what is a GPU?` → Graphics processing unit at #1 EVIDENCE-WARRANTED 1/1; Mount Kilimanjaro / Soviet Union queries unchanged (no regression). 2026-05-13 — `arborist/concepts/extract.py:acronym_parens_synonym` lands as a new corpus-agnostic extractor in `EXTRACTORS` (`evidence_kind="acronym_parens"`). Scans each doc's lead chunk for `<Multi-Word Phrase> (ACRO)` where the all-caps acronym's letters match the content-word initials of the phrase in order; emits bidirectional synonym edges between the lowercased acronym and each ≥3-char content token of the phrase. Conservative (strict 1:1 initials, function words filtered, repeated definitions deduped per doc). Closes the *retrieval-side* abbreviation gap (`CPU↔central processing unit`, `GPU↔graphics processing unit`, `RAM↔random access memory`, `FBI↔federal bureau of investigation`, `WHO↔world health organization`, …) that `link_reciprocity_synonym` can't reach because the relation lives in body text, not the wiki link graph (Wikipedia represents abbreviation→expansion as a *redirect* — not an edge). Per-shard like all `concept_relations` data; corpus-agnostic so HTML/blogs/textbooks benefit equally. Retrieval-side only — never proof-path. 8 new tests; full suite green. Closes #000050 §2a's CPU/GPU fixture rows *upstream* of vec; the Orwell-shape conceptual-allusion row remains the genuine #000050 justification. Operational follow-up (not code): `arborist concepts derive --extractor acronym_parens` on each shard. | 2026-05-13 | —         |
 | #000053  | Acronym-aware verifier content tokens | **closed · 2026-05-13** — `arborist.qa.evidence._content_tokens` now keeps all-caps 2-3-char acronyms (CPU/GPU/DNA/FBI/USB…) as content tokens instead of dropping every <4-char token; fixes the field case where "what is a CPU?" cited to "CPU design" tripped `TITLE_MISMATCH` spuriously (claim & title share "CPU" but neither registered) — also affects `SUBJECT_TOKENS_ABSENT` (Rule 9), `BARE_NAME_CLAIM`, spotlight-excerpt token pick. Versioned: `content_token_rules: "v2-acronym-aware"` in both default policies + `_VERIFIER_POLICY_FIELDS` → folds into `verifier_policy_hash`, prior cache records orphan on lookup (by design, same discipline as `base_version` / `hyphen_fold_v1`). Monotone toward *fewer* spurious demotes (only relaxes overlap checks, never tightens). 8 new tests; full suite green; `bench-qa-smoke` clean. Does NOT fix the *retrieval* abbreviation→expansion gap (`CPU`→`Central processing unit` = #000050 vec hybrid / `concepts/` synonym edges — the root cause of the satellite-article retrieval). | 2026-05-13 | —         |
 | #000052  | Relevance + coherence meta-cognition (answer-*shape* signals) | in progress — **§3.1 `diagnose_coherence` landed** (lexical, no model: `circular` / `phrase_component_reuse` / `vacuous`; in `arborist/qa/inspect.py`, surfaced via `inspect_cache_key` + `arborist inspect` `· incoherent: <kind>`; 9 tests; demote-policy hook deliberately not wired — advisory only). Joins the `diagnose_deflection` / `diagnose_metaphor_deflection` / `diagnose_title_relevance` / soft-preflight family of read-only, demote-only, never-in-proof-path sidecars; `phrase_component_reuse` catches the motivating field case (a subject quoting a phrase, a predicate reusing one of that phrase's own tokens as a bare `the <token>` referent). **Still open: (2) `diagnose_relevance`** — semantic (not just lexical) "aboutness": does the answer address the question; is each claim about its cited source? Today's checks (subject-anchor token overlap, stemmed title-stem overlap) are *lexical* and a token collision defeats them — a small *aboutness/reranker* model (NOT NLI — entailment ≠ topicality) under #000049 §7's discipline cage verbatim (demotion-only, hash-pinned, `relevance_model_version`→`governance_policy_hash` iff it touches `audit_mode`, shadow-first, `[…]` extra, the §7 #20 haystack lesson — never over the whole context); gated on evidence, travels with #000049's model question. Motivating field case (2026-05-12, fox): the `claim_lattice` query that returned *"the phrase 'Zionist entity' is sometimes used as the entity, referring to the State of Israel"* at `EVIDENCE-WARRANTED-PARTIAL 2/3` — incoherent + token-collision recombination that NLI can't catch (returns *neutral*, not *contradiction*) and both lexical relevance checks waved through. Flags an upstream retrieval ticket (polysemy / title-token-soup) as the root-cause fix, not scoped here. #000049 sibling | 2026-05-12 | —         |
 | #000051  | Federated vecpack distribution (gossip the embedding backfill) | open · awaiting go/no-go · doc-only scaffold. Makes `chunk_vecs` a distributable artifact: backfill once on any CPU box (cloud / Prometheus-Σ sweep — #000037 §3.1), publish a **vecpack** `(shard_root, vec_backend_version, [(leaf_hash, embedding_blob)…])` over the mesh wire layer, every peer pulls + bulk-loads (sub-ms/chunk on the receiver — the laptop never runs the transformer). Keyed on `leaf_hash` (portable) not `chunk_id` (shard-local). Vecpacks are **soft data** — embeddings are `UNGROUNDED`, never proof path — so a cheap structural sanity gate (chunk exists locally w/ matching leaf_hash, right blob length for (dim,quant), finite norm, backend_version matches) suffices, no Merkle-proof-grade verification needed. Supplies #000050's prereq #1 ("a vecpack exists & is imported on the bench box", not "fox embedded the corpus locally"). GPU producer (the fast path): bge-small-en-v1.5 batched on a CUDA box (4090) ≈ 10³–10⁴ chunks/s → full 6.24M-chunk corpus in *minutes*, not days — drop a CUDA `Embedder` into `default_embedder()`; CUDA stack lives only on the producer box, never in arborist's `python+sqlite3` core. The mechanism behind whitepaper §1's "the embedding pass runs off the device". #000039 / #000050 sibling | 2026-05-12 | —         |