The CaLiGraph ontology as a challenge for OWL reasoners

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URL:	http://ceur-ws.org/Vol-3123/paper3.pdf
Weitere URL:	http://ceur-ws.org/Vol-3123/
URN:	urn:nbn:de:bsz:180-madoc-619627
Dokumenttyp:	Konferenzveröffentlichung
Erscheinungsjahr:	2021
Buchtitel:	Semantic Reasoning Evaluation Challenge 2021 : proceedings of the Semantic Reasoning Evaluation Challenge (SemREC 2021), co-located with the 20th International Semantic Web Conference (ISWC 2021); virtual event, October 27th, 2021
Titel einer Zeitschrift oder einer Reihe:	CEUR Workshop Proceedings
Band/Volume:	3123
Seitenbereich:	21-31
Veranstaltungstitel:	SemREC 2021
Veranstaltungsort:	Online
Veranstaltungsdatum:	27.10.2021
Herausgeber:	Singh, Gunjan ; Mutharaju, Raghava ; Kapanipathi, Pavan
Ort der Veröffentlichung:	Aachen, Germany
Verlag:	RWTH Aachen
ISSN:	1613-0073
Verwandte URLs:	https://arxiv.org/abs/2110.05028
Sprache der Veröffentlichung:	Englisch
Einrichtung:	Fakultät für Wirtschaftsinformatik und Wirtschaftsmathematik > Data Science (Paulheim 2018-)
Bereits vorhandene Lizenz:	Creative Commons Namensnennung 4.0 International (CC BY 4.0)
Fachgebiet:	004 Informatik
Abstract:	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.
Zusätzliche Informationen:	Online-Ressource