We present FarsWikiKG, a Persian knowledge graph extracted from Wikipedia. Wikipedia infoboxes have been used as a valuable resource for building knowledge graphs in recent years. FarsWikiKG consists of more than 2 million entities, as well as 5.7 million facts about the entities. Using Wikidata, we constructed an ontology with more than 6000 classes representing entity types. As the second Persian knowledge graph, which has the ability of self-update, FarsWikiKG shows improvement on NLP tasks, especially question answering systems. Although FarsWikiKG is a dynamic knowledge graph, our evaluation shows a coverage of 90% on Persian Wikipedia pages. As Wikipedia information is constantly changing, a fixed knowledge graph can provide unstable data to the user. The proposed system, in addition to solving the problem of unstable data, reduces the need for experts to extract and construct knowledge graphs manually. Storing information in RDF as a standard method of storing knowledge graph information, FarsWikiKG allows NLP systems to run SPARQL queries on it.
