Reasoning over knowledge graphs is traditionally built upon a hierarchy of languages in the Semantic Web Stack. Starting from the Resource Description Framework (RDF) for knowledge graphs, more advanced constructs have been introduced through various syntax extensions to add reasoning capabilities to knowledge graphs. In this paper, we show how standardized semantic web technologies (RDF and its query language SPARQL) can be reproduced in a unified manner with dependent type theory. In addition to providing the basic functionalities of knowledge graphs, dependent types add expressiveness in encoding both entities and queries, explainability in answers to queries through witnesses, and compositionality and automation in the construction of witnesses. Using the Coq proof assistant, we demonstrate how to build and query dependently typed knowledge graphs as a proof of concept for future works in this direction.

中文翻译：

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依赖类型知识图谱

对知识图的推理传统上建立在语义 Web 堆栈中的语言层次结构上。从知识图谱的资源描述框架 (RDF) 开始，通过各种语法扩展引入了更高级的构造，以向知识图谱添加推理功能。在本文中，我们展示了标准化语义 Web 技术（RDF 及其查询语言 SPARQL）如何通过依赖类型理论以统一的方式重现。除了提供知识图谱的基本功能外，依赖类型还增加了编码实体和查询的表达能力、通过见证人对查询的回答的可解释性以及见证人构建的组合性和自动化。使用 Coq 证明助手，