Automatic compilation of language resources for named entity recognition in Turkish by utilizing Wikipedia article titles

We present an automatic approach to compile language resources for named entity recognition (NER) in Turkish by utilizing Wikipedia article titles. First, a subset of the article titles is annotated with the basic named entity types. This subset is then utilized as training data to automatically classify the remaining titles by employing the k-nearest neighbor algorithm, leading to the construction of a significant lexical resource set for Turkish NER. Experiments on different text genres are conducted after extending an existing NER system with the resources and the results obtained confirm that the resources contribute to NER on different genres. (C) 2015 Elsevier B.V. All rights reserved.