A Morpho-Syntactically Informed LSTM-CRF Model for Named Entity Recognition

Lilia Simeonova, Kiril Simov, Petya Osenova +1

We propose a morphologically informed model for named entity recognition, which is based on LSTM-CRF architecture and combines word embeddings, Bi-LSTM character embeddings, part-o…