The CaLiGraph Ontology as a Challenge for OWL Reasoners
This addresses a specific bottleneck in ontology reasoning for knowledge graph researchers, but it is incremental as it focuses on benchmarking rather than a new method.
The paper tackles the challenge of reasoning over the CaLiGraph knowledge graph, which has a large A-box and rich ontology, and finds that existing reasoning systems inadequately support materializing owl:hasValue constraints, providing benchmark subsets for performance analysis.
CaLiGraph is a large-scale cross-domain knowledge graph generated from Wikipedia by exploiting the category system, list pages, and other list structures in Wikipedia, containing more than 15 million typed entities and around 10 million relation assertions. Other than knowledge graphs such as DBpedia and YAGO, whose ontologies are comparably simplistic, CaLiGraph also has a rich ontology, comprising more than 200,000 class restrictions. Those two properties - a large A-box and a rich ontology - make it an interesting challenge for benchmarking reasoners. In this paper, we show that a reasoning task which is particularly relevant for CaLiGraph, i.e., the materialization of owl:hasValue constraints into assertions between individuals and between individuals and literals, is insufficiently supported by available reasoning systems. We provide differently sized benchmark subsets of CaLiGraph, which can be used for performance analysis of reasoning systems.