Hierarchical Representations of Freebase Topics

The dataset contains more than 21M hierarchical relationships about ≈10M topics extracted from Freebase knowledgebase. The topics span the various categories of Freebase including Science &amp; Technology, Arts &amp; Entertainment, Sports, Society, Products &amp; Services, Transportation, Time &amp; Space, Special Interests, and Commons. The relationships describe the hierarchies of topics in terms of Types, Domains, and Categories. For example, ‘Albert Einstein’ can be found as a topic that is a sub-class of ‘Person’, belonging to the ‘People’ domain and ‘Society’ category. While another entity named as ‘Albert Einstein’ can also be found as a sub-class of ‘Book’, belonging to the ‘Books’ domain and ‘Arts &amp; Entertainment’ category. The dataset is published in JSON and CSV formats, sample files are provided to help explore how the dataset is structured.<br> The dataset is believed to be useful for studying the inter-related connections among topics in different domains of knowledge. The first author may be contacted at ([e-mail]) for more information. The following paper may kindly be cited in case of using the dataset. Mahmoud Elbattah, Mohamed Roushdy, Mostafa Aref, Abdel-Badeeh M. Salem. “Large-Scale Entity Clustering Using Graph-Based Structural Similarity within Knowledge Graphs”, Big Data Analytics: Tools, Technology for Effective Planning, CRC Press. https://www.researchgate.net/publication/321716589_Large-Scale_Entity_Clustering_Based_on_Structural_Similarity_within_Knowledge_Graphs