semantica/docs/reference/conflicts.md

title, description, icon

title	description	icon
Conflicts Module	Multi-source conflict detection and resolution — value, type, temporal, and logical conflicts.	triangle-exclamation

Comprehensive conflict detection and resolution for data discrepancies across multiple sources.

---

Overview

When multiple sources disagree on the same fact, the Conflicts Module detects and resolves the conflict rather than silently picking one value.

Detection types: value, type, temporal, and logical conflicts.

---

ConflictDetector

from semantica.conflicts import ConflictDetector

detector = ConflictDetector()
conflicts = detector.detect_conflicts(kg)

for conflict in conflicts:
    print(f"Conflict on '{conflict.entity}' — {conflict.attribute}")
    print(f"  Source A: {conflict.value_a} (from {conflict.source_a})")
    print(f"  Source B: {conflict.value_b} (from {conflict.source_b})")
    print(f"  Type: {conflict.conflict_type}")

---

Detection Types

# Detect specific types only
conflicts = detector.detect_conflicts(
    kg,
    types=["value", "temporal"]   # value | type | temporal | logical
)

Value conflicts — same entity, same attribute, different values across sources. Type conflicts — same entity classified as different types in different sources. Temporal conflicts — overlapping validity windows with contradictory facts. Logical conflicts — facts that violate ontology axioms or constraints.

---

Conflict Resolution

from semantica.conflicts import ConflictResolver

resolver = ConflictResolver()
resolved_kg = resolver.resolve(
    kg,
    conflicts,
    strategy="most_recent"   # see strategies below
)

Resolution strategies:

Strategy	Description
most_recent	Prefer the most recently updated fact
most_reliable	Prefer the source with the highest reliability score
majority_vote	Use the value agreed upon by most sources
highest_confidence	Prefer the fact with the highest confidence score
flag_for_review	Mark conflicting facts for manual resolution

---

Source Reliability Scoring

resolver = ConflictResolver(
    source_reliability={
        "pubmed": 0.95,
        "wikipedia": 0.80,
        "user_input": 0.60
    }
)
resolved_kg = resolver.resolve(kg, conflicts, strategy="most_reliable")

---

Conflict Report

report = detector.generate_report(conflicts)
print(f"Total conflicts: {report.total}")
print(f"By type: {report.by_type}")
print(f"Most conflicted entities: {report.top_entities[:5]}")

report.export("conflicts.json")

---

See Also

Resolve duplicate entities before conflict detection. Logical conflicts use ontology axioms. Track which source each conflicting fact came from. The graph being checked for conflicts.