YAGO 4.5: A Large and Clean Knowledge Base with a Rich Taxonomy

TL;DR

YAGO 4.5 enhances the YAGO knowledge base by integrating a significant portion of Wikidata's taxonomy, resulting in a large, clean, and logically consistent resource that improves information retrieval and reasoning capabilities.

Contribution

The paper introduces YAGO 4.5, a new version that combines YAGO 4 with a substantial part of Wikidata's taxonomy while maintaining logical consistency.

Findings

YAGO 4.5 is larger and more informative than previous versions.

Intrinsic and extrinsic evaluations demonstrate improved reasoning and retrieval.

The resource is logically consistent and suitable for knowledge-intensive tasks.

Abstract

Knowledge Bases (KBs) find applications in many knowledge-intensive tasks and, most notably, in information retrieval. Wikidata is one of the largest public general-purpose KBs. Yet, its collaborative nature has led to a convoluted schema and taxonomy. The YAGO 4 KB cleaned up the taxonomy by incorporating the ontology of Schema.org, resulting in a cleaner structure amenable to automated reasoning. However, it also cut away large parts of the Wikidata taxonomy, which is essential for information retrieval. In this paper, we extend YAGO 4 with a large part of the Wikidata taxonomy - while respecting logical constraints and the distinction between classes and instances. This yields YAGO 4.5, a new, logically consistent version of YAGO that adds a rich layer of informative classes. An intrinsic and an extrinsic evaluation show the value of the new resource.