Freebase-triples: A Methodology for Processing the Freebase Data Dumps

Abstract

The Freebase knowledge base was a significant Semantic Web and linked data technology during its years of operations since 2007. Following its acquisition by Google in 2010 and its shutdown in 2016, Freebase data is contained in a data dump of billions of RDF triples. In this research, an exploration of the Freebase data dumps will show best practices in understanding and using the Freebase data and also present a general methodology for parsing the linked data. The analysis is done with limited computing resources and the use of open-source Unix-like tools. The results showcase the efficiency of the technique and highlight redundancies in the data, with the possibility of restructuring nearly 60% of the original data. As an archival dataset that has not changed since 2015, Freebase's semantic structured data has applications in other prominent fields, such as information retrieval (IR) and knowledge-based question answering (KBQA). Freebase can also serve as a gateway to other structured datasets, such as DBpedia, Wikidata, and YAGO.