arXiv:2610.33018v1 Announce Type: new Abstract: Scholarly Knowledge Graphs (SKGs) support literature search, scientific discovery, and agent-assisted research. Yet, most approaches to SKG construction pre-specify the knowledge unit to be represented, typically named scholarly entities or contribution-level statements, and retain only the publication content expressible through that unit. This choice produces two dominant yet distinct paradigms: concept-centric SKGs that preserve entities and local relations, and statement-centric SKGs that capture high-level discourse in sentences. In both cases, the graph reflects a chosen extraction target rather than how a paper constructs and communicates knowledge. We introduce SUDO, the Scholarly Upper Discourse Ontology, which defines how knowledge
arXiv：2610.33018v1 发布类型：新 摘要：学术知识图谱（SKGs）支持文献检索、科学发现以及智能体辅助研究。然而，大多数构建学术知识图谱的方法都预先规定了所要表示的知识单元，通常以学术实体或贡献层面的陈述为名，并且仅保留能够通过该单元表达的出版内容。这种选择导致了两种主导但截然不同的范式：以概念为中心的学术知识图谱侧重于保存实体及其局部关系，而以陈述为中心的学术知识图谱则聚焦于以句子形式呈现的高层次话语。在这两种情况下，图谱反映的都是所选定的抽取目标，而非论文如何构建并传达知识。我们提出了 SUDO——学术上层话语本体，它定义了知识的……
