Two-stage Approach to Named Entity Recognition using Wikipedia and DBpedia

In natural language understanding, extraction of named entity (NE) mentions in given text and classification of the mentions into pre-defined NE types are important processes. Most NE recognition (NER) relies on resources such as a training corpus or NE dictionary, but collecting them manually is laborious and time-consuming. This paper proposes a two-stage approach based on nothing but Wikipedia and DBpedia to implement NER. This paper also addresses technical problems in developing Korean NER. In experiments, the proposed method can recognize NEs in short question sentences with 14.2% errors.1