In this paper, we propose a novel method to automatically build a named entity corpus based on the DBpedia ontology. Since most
of named entity recognition systems require time and effort consuming annotation tasks as training data. Work on NER has thus for
been limited on certain languages like English that are resource-abundant in general. As an alternative, we suggest that the NE corpus
generated by our proposed method, can be used as training data. Our approach introduces Wikipedia as a raw text and uses the DBpedia
data set for named entity disambiguation. Our method is language-independent and easy to be applied to many different languages
where Wikipedia and DBpedia are provided. Throughout the paper, we demonstrate that our NE corpus is of comparable quality even to
the manually annotated NE corpus.