Provenance-enhanced statements of the form "according to $X$, $\varphi$" are pervasive in contemporary knowledge graphs, especially in domains where graph content primarily represents claims, interpretations, and hypotheses (\emph{capta}) rather than observer-independent facts (\emph{data}). Current provenance models can record who asserted what, but they typically treat provenance as semantically neutral, leaving underspecified how attributed claims relate to factual commitment, to one another, and to reasoning. In this paper we introduce DEC, a framework that interprets provenance predicates as indicators of epistemic stance and groups provenance-homogeneous sets of statements into \emph{cognitive worlds}. Drawing on cognitive modal logics (doxastic, epistemic, and conjectural), DEC characterizes locality, rationality, and controlled permeation between cognitive worlds and a distinguished factual core ("reality"), thereby enabling principled reasoning over attributed content without collapsing disagreements into inconsistencies. We formalize a DEC interpretation for RDF datasets that is conservative over RDF~1.2 semantics, clarify the role of intensionality and identity (including the Superman paradox), and illustrate the approach on common Semantic Web representations (named graphs, quoted triples/RDF-star, and reification). Finally, we describe our prototype DEC reasoner implemented as a Fuseki dataset module, supporting controlled factualisation and explicit detection of disagreements and delusions.

翻译：形式为“根据 $X$，$\varphi$”的带来源增强的陈述在当代知识图谱中普遍存在，特别是在图谱内容主要表示主张、解释和假设（\emph{capta}）而非观察者独立事实（\emph{data}）的领域中。当前来源模型可以记录谁断言了什么，但它们通常将来源视为语义中性的，未能充分说明所归因的主张与事实承诺、彼此之间以及推理之间的关系。在本文中，我们引入DEC框架，该框架将来源谓词解释为认知立场的指示符，并将来源同质的陈述组划分为\emph{认知世界}。基于认知模态逻辑（信念逻辑、知识逻辑和推测逻辑），DEC刻画了认知世界与一个杰出的事实核心（“现实”）之间的局部性、合理性和受控渗透，从而能够对归因内容进行有原则的推理，而不会将分歧归约为不一致。我们为RDF数据集形式化了一种保守于RDF 1.2语义的DEC解释，阐明了内涵性和同一性（包括超人悖论）的作用，并基于常见的语义网表示（命名图、引用三元组/RDF-star和具体化）说明了该方法。最后，我们描述了作为Fuseki数据集模块实现的原型DEC推理器，该推理器支持受控事实化以及分歧和妄想的有意识检测。