Building an Indonesian named entity recognizer using Wikipedia and DBPedia

Abstract

This paper describes the development of an Indonesian NER system using online data such as Wikipedia 1 and DBPedia 2. The system is based on the Stanford NER system [8] and utilizes training documents constructed automatically from Wikipedia. Each entity, i.e. word or phrase that has a hyperlink, in the Wikipedia documents are tagged according to information that is obtained from DBPedia. In this very first version, we are only interested in three entities, namely: Person, Place, and Organization. The system is evaluated using cross fold validation and also evaluated using a gold standard that was manually annotated. Using cross validation evaluation, our Indonesian NER managed to obtain precision and recall values above 90%, whereas the evaluation using gold standard shows that the Indonesian NER achieves high precision but very low recall.