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.

翻译：知识库在许多知识密集型任务中具有广泛应用，最显著的是信息检索领域。维基数据是最大的公共通用知识库之一，但其协作特性导致了层次结构与分类体系的复杂性。YAGO 4通过整合Schema.org的本体论，清理了分类体系，形成了更利于自动推理的清晰结构，但同时也删除了维基数据分类体系中大量对信息检索至关重要的内容。本文在保留逻辑约束及类与实例区分的前提下，将维基数据分类体系的主要部分扩展至YAGO 4，从而构建出逻辑一致的YAGO 4.5版本。该版本新增了信息量丰富的类层次结构，通过内在评估与外在评估共同验证了新资源的价值。