Classifying articles in English and German Wikipedia
Named Entity (NE) information is critical for Information Extraction (IE) tasks. However, the cost of manually annotating sufficient data for training purposes, especially for multiple languages, is prohibitive, meaning automated methods for developing resources are crucial. We investigate the automatic generation of NE annotated data in German from Wikipedia. By incorporating structural features of Wikipedia, we can develop a German corpus which accurately classifies Wikipedia articles into NE categories to within 1% F -score of the state-of-the-art process in English.