  In recent years, an increasing amount of knowledge graphs (KGs) have been
created as a means to store cross-domain knowledge and billion of facts, which
are the basis of costumers' applications like search engines. However, KGs
inevitably have inconsistencies such as duplicates that might generate
conflicting property values. Duplication detection (DD) aims to identify
duplicated entities and resolve their conflicting property values effectively
and efficiently. In this paper, we perform a literature review on DD methods
and tools, and an evaluation of them. Our main contributions are a performance
evaluation of DD tools in KGs, improvement suggestions, and a DD workflow to
support future development of DD tools, which are based on desirable features
detected through this study.
