sudacode
7442e4266c
- Treat kana-only tokens with surrounding subtitle punctuation (…, ―, etc.) as kana-only so they are not promoted to N+1 targets - Exclude unknown tokens filtered from N+1 targeting from the minSentenceWords count so filtered kana-only unknowns cannot satisfy sentence length threshold - Add regression tests for kana-only candidate suppression and filtered-unknown padding cases
3.7 KiB
id, title, status, assignee, created_date, updated_date, labels, dependencies, priority
| id | title | status | assignee | created_date | updated_date | labels | dependencies | priority | |||
|---|---|---|---|---|---|---|---|---|---|---|---|
| TASK-310 | Suppress N+1 highlight for kana-only candidate sentences | Done |
|
2026-04-28 06:55 | 2026-04-28 07:04 |
|
medium |
Description
Reduce noisy N+1 subtitle annotations when the only unknown candidates in a sentence are kana-only hiragana or katakana words, such as mostly-kana subtitle lines where highlighting a particle/helper-like token is low value.
Acceptance Criteria
- #1 N+1 annotation does not mark a kana-only unknown target when all N+1 candidates in the sentence are kana-only.
- #2 N+1 annotation continues to mark kanji or mixed-script unknown targets in otherwise eligible sentences.
- #3 A focused regression test covers the kana-only candidate case.
- #4 N+1 minimum sentence word count excludes tokens stripped by the subtitle annotation filter, so filtered grammar/noise tokens cannot satisfy minSentenceWords.
Implementation Plan
- Keep the existing N+1 target eligibility guard: kana-only subtitle surfaces do not become N+1 targets.
- Add a focused regression in src/core/services/tokenizer/annotation-stage.test.ts proving annotation-filtered tokens do not count toward ankiConnect.nPlusOne.minSentenceWords.
- Verify the new regression fails before code changes.
- Patch src/token-merger.ts so the N+1 minimum sentence word count uses the same subtitle-annotation eligibility filter as annotation rendering, excluding filtered particles/auxiliaries/noise from the count.
- Re-run focused tokenizer tests, then update TASK-310 acceptance criteria and final notes.
Implementation Notes
Initial context: current token-merger has an existing surface-level kana-only guard in isNPlusOneCandidateToken, added in commit 9e4ad907. Need decide whether to broaden behavior to lookup/headword forms or verify current behavior only.
Implemented by treating kana-only N+1 candidates as kana-only even when their token surface includes surrounding subtitle punctuation such as ellipsis or dashes. Focused regression was red before the token-merger change: スイッチ… was marked true, then passed after the guard update. test:env initially hit an unrelated immersion-tracker active_days timing/order failure and Bun follow-on loader error; the failing test passed in isolation and the full test:env rerun passed.
Reopened for follow-up scope: minSentenceWords must count annotation-eligible tokens only, not tokens stripped from annotation metadata.
Implemented follow-up minSentenceWords behavior: unknown tokens filtered from N+1 targeting no longer contribute to sentence length; known eligible tokens and true N+1 candidates still count.
Final Summary
Changed N+1 sentence-length counting so minSentenceWords only counts known eligible words and actual N+1 target candidates. Unknown tokens filtered from N+1 targeting, including kana-only unknowns, no longer pad a sentence into eligibility. Existing annotation-filtered particles/auxiliaries remain excluded. Added regression coverage for the filtered unknown padding case while preserving kanji/mixed-script target behavior.
Verification: new regression failed before implementation; bun test src/core/services/tokenizer/annotation-stage.test.ts -t "N\\+1" pass; full bun test src/core/services/tokenizer/annotation-stage.test.ts pass; bun test src/core/services/tokenizer.test.ts -t "N\\+1" pass; bun run typecheck pass.