Disjointness Violations in Wikidata

TL;DR

This paper analyzes disjointness violations in Wikidata, identifying patterns and causes of contradictions, and proposes methods for detection and correction to improve data consistency.

Contribution

It provides a detailed analysis of disjointness violations in Wikidata, categorizes causes, and offers formulas and strategies for better modeling and fixing conflicts.

Findings

Identified common patterns causing disjointness violations.

Developed SPARQL-based methods to detect conflicting statements.

Suggested improvements for disjointness modeling in Wikidata.

Abstract

Disjointness checks are among the most important constraint checks in a knowledge base and can be used to help detect and correct incorrect statements and internal contradictions. Wikidata is a very large, community-managed knowledge base. Because of both its size and construction, Wikidata contains many incorrect statements and internal contradictions. We analyze the current modeling of disjointness on Wikidata, identify patterns that cause these disjointness violations and categorize them. We use SPARQL queries to identify each ``culprit'' causing a disjointness violation and lay out formulas to identify and fix conflicting information. We finally discuss how disjointness information could be better modeled and expanded in Wikidata in the future.