A Morpho-Syntactically Informed LSTM-CRF Modelfor Named Entity Recognition
Table 5: Comparing the previous state-of-the-art results to our best morphologically informed Bi-LSTM-CRF model.
['[BOLD] Model', '[BOLD] F1']
They achieved an F1 score of 89.4% by sing regular expressions, gazetteers and non-local morpho-syntactic characteristics. Our model improves this to 92.20% without using any external resources.