Named Entity Recognition over FBNER: A New Facebook Dataset in Turkish

In this paper, we introduce a new Named Entity Recognition (NER) dataset of Facebook messages written in the Turkish language. We also employ a Conditional Random Fields based NER system to discover named entities from Facebook messages. Our system achieves an F1 score of 0.713 when training and test sets include Facebook posts. We also obtained an F1 score of 0.599 when the training set is from the news domain. A strength of this research is that it is one of the first studies in this field that focuses on NER over Turkish Facebook messages. This is because performing NER on user-generated content turns into a very challenging task since such informal contents are often noisy texts that have arammatical and spelling errors.