We propose a new framework for combining entity resolution and query answering in knowledge bases (KBs) with tuple-generating dependencies (tgds) and equality-generating dependencies (egds) as rules. We define the semantics of the KB in terms of special instances that involve equivalence classes of entities and sets of values. Intuitively, the former collect all entities denoting the same real-world object, while the latter collect all alternative values for an attribute. This approach allows us to both resolve entities and bypass possible inconsistencies in the data. We then design a chase procedure that is tailored to this new framework and has the feature that it never fails; moreover, when the chase procedure terminates, it produces a universal solution, which in turn can be used to obtain the certain answers to conjunctive queries. We finally discuss challenges arising when the chase does not terminate.
翻译:我们提出了一个新的框架,将实体的解决方案和在知识基础中回答问题(KBs)与产生结果的相互依存关系(tgds)和产生平等依赖关系(egds)作为规则结合起来。我们从涉及实体等同类别和一系列价值的特殊情况来定义KB的语义。从直觉上看,前者收集了所有实体对同一个现实世界对象的描述,而后者则收集了所有属性的替代值。这一方法使我们既可以解决实体问题,也可以绕过数据中可能出现的不一致之处。然后,我们设计了一种针对这一新框架的追逐程序,其特征是永远不变的;此外,当追逐程序终止时,它产生一种普遍的解决办法,这反过来可以用来获得对共质询问的某些答案。我们最后讨论在追逐不终止时出现的挑战。</s>