From Line Knowledge Digraphs to Sheaf Semantics: A Categorical Framework for Knowledge Graphs

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1. Verfasser: Boudourides, Moses
Format: Preprint
Veröffentlicht: 2026
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author Boudourides, Moses
author_facet Boudourides, Moses
contents This paper proposes a categorical framework for knowledge graphs linking combinatorial graph structure with topos-theoretic semantics. Knowledge graphs are represented as labelled directed multigraphs and analysed through incidence matrices and line knowledge digraph constructions. The graph induces a free category whose morphisms correspond to relational paths. To model context-dependent meaning, a Grothendieck topology is defined on the free category generated by the graph leading to a topos of sheaves that supports local-to-global semantic reasoning. The framework connects graph-theoretic structure, categorical composition, and sheaf semantics in a unified mathematical model for contextual relational reasoning.
format Preprint
id arxiv_https___arxiv_org_abs_2603_05685
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle From Line Knowledge Digraphs to Sheaf Semantics: A Categorical Framework for Knowledge Graphs
Boudourides, Moses
Social and Information Networks
This paper proposes a categorical framework for knowledge graphs linking combinatorial graph structure with topos-theoretic semantics. Knowledge graphs are represented as labelled directed multigraphs and analysed through incidence matrices and line knowledge digraph constructions. The graph induces a free category whose morphisms correspond to relational paths. To model context-dependent meaning, a Grothendieck topology is defined on the free category generated by the graph leading to a topos of sheaves that supports local-to-global semantic reasoning. The framework connects graph-theoretic structure, categorical composition, and sheaf semantics in a unified mathematical model for contextual relational reasoning.
title From Line Knowledge Digraphs to Sheaf Semantics: A Categorical Framework for Knowledge Graphs
topic Social and Information Networks
url https://arxiv.org/abs/2603.05685