发表机构
TU Dresden（德累斯顿工业大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对RDF规则结合默认否定的难题，提出链分层条件保证良好语义，确保导出唯一精简的RDF图，并给出原型实现。
AI 中文摘要
将RDF规则语言（如N3或SHACL规则）与默认否定相结合颇具挑战性。现有的否定分层方法通常不适用于RDF规则，因为单个三元组无法提供足够信息来合理限制潜在依赖关系；规则头部的空白节点进一步增加了复杂度，规则应用顺序可能决定新值是否生成，进而改变带否定规则的适用性。为解决这些未决问题，我们提出链分层这一稳健的新条件，它能为带否定的RDF规则及一般存在规则保证良好的语义。该条件结合了对潜在多步推导的精细分析，以及用完整性约束丢弃不可能情况的机制。按符合链分层的任意顺序应用规则，可保证导出的RDF图在常用的失败即否定语义下是唯一、精简且合理的。为展示实用性，我们还提供了原型实现。
英文摘要
Combining RDF rule languages, such as N3 or SHACL Rules, with default negation is challenging. Existing methods to stratify negation often fail for RDF rules, since individual triples do not carry enough information to meaningfully restrict potential dependencies. Blank nodes in rule heads further complicate the matter, since the order of rule applications may determine whether new values are created, which in turn can change the applicability of rules with negation. To solve these open problems, we propose chain stratification as a robust new condition that guarantees a well-behaved semantics for RDF rules with negation, and existential rules in general. Our condition combines an elaborate analysis of potential multistep derivations with a mechanism for using integrity constraints to discard impossible cases. Applying rules in any order that respects chain stratification is guaranteed to derive an RDF graph that is unique, lean, and justified under the usual negation-as-failure semantics. To show the practicality, we also provide a prototype implementation.
CommentsTechnical report of our ISWC'26 paper
