A Note on General Statistics of Publicly Accessible Knowledge Bases
Feixiang Wang, Yixiang Fang, Yan Song, Shuang Li, Xinyun Chen

TL;DR
This paper summarizes the key statistics of various open-source knowledge bases, aiding researchers and users in understanding and utilizing these resources more effectively.
Contribution
It provides a comprehensive overview of the size and structure of publicly accessible knowledge bases, which was previously lacking in consolidated form.
Findings
Knowledge bases vary widely in size and complexity.
Statistics include object counts, relation types, and object types.
The overview facilitates better research and application of knowledge bases.
Abstract
Knowledge bases are prevalent in various domains and have been widely used in a large number of real applications such as applications in online encyclopedia, social media, biomedical fields, bibliographical networks. Due to their great importance, knowledge bases have received much attention from both the academia and industry community in recent years. In this paper, we provide a summary of the general statistics of several open-source and publicly accessible knowledge bases, ranging from the number of objects, relations to the object types and the relation types. With such statistics, this concise note can not only help researchers form a better and quick understanding of existing open accessible knowledge bases, but can also guide the general audience to use the resource effectively when they conduct research with knowledge bases.
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Taxonomy
TopicsSemantic Web and Ontologies · Web Data Mining and Analysis · Topic Modeling
