Topic hubs in /graph are built from case_law.subject_tags. The documented
extraction contract (precedent_library tool examples: קווי_בניין,
מועד_קביעת_שומה) and ~99% of the corpus store plain multi-word Hebrew tags
with underscores between words ("היטל_השבחה"). A single case (8126-03-25,
יעקב עמיאל) was tagged with spaces ("היטל השבחה"), which the graph renders as
a SECOND, distinct topic hub — a duplicate of the underscore form. The data
was normalized separately; this enforces the convention at the source so no
write path can re-introduce the split.
_normalize_subject_tags() is applied at the three (and only) case_law write
chokepoints in db.py — create_external_case_law, create_internal_committee_decision,
update_case_law — so the rule cannot be bypassed (G1: normalize at source, not
in the read/graph path). Tags carrying punctuation/digits/dashes
(e.g. "פטור מותנה — סעיף 19(ג)") are left untouched; only plain Hebrew word
phrases ([א-ת]+ separated by spaces) are converted. Also dedups post-normalize.
digests.subject_tags (TEXT[], a different graph layer) and canonical_halachot
are intentionally out of scope.
Invariants: maintains G1 (fix at source, not in the read projection),
G2 (graph_api stays a pure read projection — no parallel normalization there).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Chaim
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