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A name model reads many business names as surnames. Measured with
privacy-filter-multilingual on 24 synthetic German receipts and
invoices: the supplier name ("Hotel Seeblick", "Café Lindenhof", ...)
was masked as LASTNAME (0.78-0.98) or FIRSTNAME in 9 of 12 receipts
that carried one. The supplier is exactly what the upstream model needs
to categorise a receipt, and no score floor helps at those confidences.
pii_detection.protected_terms (inline) and
pii_detection.protected_terms_files (files inside the models path, one
term per line, '#' comments, re-read when size or mtime change) list
values that must pass unchanged. Each whole-word, case-insensitive
occurrence is replaced by a neutral placeholder before the detector
runs; every detection is mapped back onto the original text with the
placeholder parts cut out, so a protected term is never masked or
blocked, the detector never sees it as context, and event offsets keep
addressing the original text. A word extension (extend_to_next_word)
is dropped rather than run into a protected term.
Terms shorter than three characters are ignored. A missing or
unreadable file is logged and skipped: fewer protected terms means more
masking, never less. Paths are verified to stay inside the models path.
Opt-in, empty by default. Covered by Ginkgo specs in
core/services/routing/pii/protected_test.go (detector-visible text,
exact restoration, straddling detections, whole-word/case/line-wrap
matching, the segment path, file loading and reload), a YAML round-trip
spec, registry entries and the middleware/model-configuration docs.
Assisted-by: Claude Code:claude-opus-5-5
Signed-off-by: Stefan Walcz <stefan.walcz@walcz.de>
(cherry picked from commit 01f71772a5)