Coverage-discount guard for homograph false positives
a null/negative result — published in full.
Hypothesis
Discounting a recommendation’s confidence by how much of the query the matched pattern explains ("coverage") will eliminate confident homograph false positives (e.g. "budget my salary" → Crawl Budget).
Method
Add a coverage factor to matchConfidence, gated to low-overlap queries. Sweep COVERAGE_EXP ∈ {0,0.5,1,1.5,2} × overlap-gate {0.5–0.8} over a 500-query adversarial set. Compare homograph FP, answer recall, ECE, and check flagship queries for regression.
Dataset
500-query adversarial sweep (18 homographs, GEO/SEO/commercial in-scope, foreign out-of-scope).
Metrics
| homograph FP rate | ≤ 1% |
| answer recall | ≥ 80% |
| flagship-query regression | none |
Result
Decision
REJECTED. No lexical operating point separates homographs from legitimate low-overlap GEO queries. Gate disabled by default; matchCoverage retained as telemetry.
Lessons learned
- Homograph disambiguation is a semantic problem; lexical coverage cannot solve it without refusing flagship queries.
- A rejected experiment is a result: it redirected effort to embeddings (EXP-0003) with evidence instead of guesswork.
Confidence
HIGH
Evidence
500-query sweep —bench/history (calib-eval)confidence model — docs/kos-confidence-model.md