Canonicalizing Knowledge Base Literals [chapter]

Jiaoyan Chen, Ernesto Jiménez-Ruiz, Ian Horrocks
2019 Lecture Notes in Computer Science  
Ontology-based knowledge bases (KBs) like DBpedia are very valuable resources, but their usefulness and usability are limited by various quality issues. One such issue is the use of string literals instead of semantically typed entities. In this paper we study the automated canonicalization of such literals, i.e., replacing the literal with an existing entity from the KB or with a new entity that is typed using classes from the KB. We propose a framework that combines both reasoning and machine
more » ... learning in order to predict the relevant entities and types, and we evaluate this framework against state-of-the-art baselines for both semantic typing and entity matching.
doi:10.1007/978-3-030-30793-6_7 fatcat:b26y7ew5lbcpho6ftvdmwdkcy4