Abstract
Named Entity Recognition (NER) is an important task in Natural Language Processing, Data Mining and Information Extraction areas since 1990's. While NER is a succesfully solved problem in English, it is still a hot topic in agglutinative languages like Turkish, Czech, Finnish languages. With the scope of this study we focus on Bidirectional Long Short-Term Memory (BLSTM) neural network models to solve NER problem. We suggest a succesful implementation of Deep Bidirectional Long Short Term Memory (DBLSTM) which reaches %93.69 F1 score, which is state-of-the-art result for Named Entity Recognition in Turkish.
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