Does Higher Order LSTM Have Better Accuracy for Segmenting and Labeling Sequence Data?
Table 6: Dutch-NER: Comparison with state-of-the-art models. GillickBVS15 reported a F1-score of 82.84 in their work, but this result is based on multilingual resources.
['[BOLD] Dutch-NER', '[BOLD] F1']
\newciteGillickBVS15 keeps the best result of Dutch NER. However, the model is trained on four languages. With the monolingual setting, their model achieves 78.08 on F1 score. Another competitive result is reported in the work of \newciteLampleBSKD16. Their model is a BiLSTM-CRF model with an external LSTM layer to extract character-level representations of words. Our model gets the best score when there is no extra resources.