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Knowledge bases are considered as one of the most important factors in the development of internet and its future. In this regard, the Persian knowledge graph project has been implemented using Semantic Web and Linked Data. The data model in Semantic Web is RDF (Resource Description Framework) which is a graph, therefore, the structure of the project is based on an RDF model that is constituted of many facts including subjects, predicates and objects. This project extracts knowledge from many resources including Persian Wikipedia, raw texts, web tables and etc., but its main focus is on Wikipedia.
Up to now, over 6.5 million facts describing about 500000 entities have been extracted. The DBpedia’s ontology including 732 classes have been applied to the project. This ontology have been expanded by adding 25 classes according to Persian entities. In addition, 800 Wikipedia templates and more than 2000 properties has been mapped to the ontology by human experts. As far as data storage system is considered, two levels are designed for metadata and data triples.
In general, This project aims to produce a knowledge graph containing high precision data to improve the results of search engines.