A Named Entity Recognition approach for Albanian
Marjana Prifti Skënduli, Marenglen Biba · 2013
Named Entity Recognition (NER) deals with identifying personal, geographical, organizational or other entity types in a raw text. In this paper we propose the first NER model for the Albanian language. Our model is based on the maximum entropy approach. We manually annotate a corpus in the historical and political domains and train the models to generate classifiers that are able to recognize relevant entities in the text. We achieve good performance for precision and recall on the selected domains, despite the scarcity of Albanian corpora and the fact that this paper marks the first NER research for the Albanian language. Experiments demonstrate that the models can be further improved if richer training corpus is provided.