YAGO 4.5: A Large and Clean Knowledge Base with a Rich Taxonomy
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
JointRank: Rank Large Set with Single Pass
From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning Agents
DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents
Exp4Fuse: A Rank Fusion Framework for Enhanced Sparse Retrieval using Large Language Model-based Query Expansion
From Token to Action: State Machine Reasoning to Mitigate Overthinking in Information Retrieval
Retrieval Augmented Generation based Large Language Models for Causality Mining
토론
이 논문과 연결된 포럼 글이 아직 없습니다.