Neural Modeling for Named Entities and Morphology (NEMO{}^{2})
Table 6: Token-Level Eval. on Dev by Entity Category w/ fastText. Char CNN for morph, LSTM for tok.
['[EMPTY]', 'PER', 'ORG', 'GPE', 'LOC', 'FAC', 'WOA', 'EVE', 'ANG', 'DUC']
Morpheme based models show a very significant advantage for the most common category, Person, and a slight advantage in Org. Morpheme models performance suffered the most in GPE from realistic MD, thus token-based models perform slightly better. Token-based also performed better on Loc. In the rarer categories performance was very low for all models.