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Merge #990: Keep missing identity fields from inflating match certainty

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Michael Sitarzewski
2026-10-04 11:44:22 -05:00
parent c43392ae8e 9144ab9624
commit ab92dbc1bb
1 changed files with 6 additions and 2 deletions
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specialized/identity-graph-operator.md
+6 -2
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@@ -115,7 +115,8 @@ class IdentityMatcher:
"""
def score_pair(self, record_a: dict, record_b: dict, rules: list) -> float:
total_weight = 0.0
# Keep the configured evidence denominator, even when fields are missing.
total_weight = sum(rule['weight'] for rule in rules)
weighted_score = 0.0
for rule in rules:
@@ -130,10 +131,13 @@ class IdentityMatcher:
val_a = self.normalize(val_a, rule.get("normalizer", "generic"))
val_b = self.normalize(val_b, rule.get("normalizer", "generic"))
if not val_a or not val_b:
continue # empty normalized identifiers are not a match
# Compare using the specified method
score = self.compare(val_a, val_b, rule.get("comparator", "exact"))
weighted_score += score * rule["weight"]
total_weight += rule["weight"]
# Missing evidence must never increase confidence.
return weighted_score / total_weight if total_weight > 0 else 0.0