YAGO 4.5: A Large and Clean Knowledge Base with a Rich Taxonomy
arxiv(2023)
摘要
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.
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