Morphosyntactic Tagging with a Meta-BiLSTM Modelover Context Sensitive Token Encodings
Table 6: F1 score for selected languages on sentence vs. word level character models for the prediction of morphology using late integration.
['[BOLD] dev. set', 'word char model', 'sentence char model']
We compared the setup with sentence-based character context We selected for these experiments a number of morphological rich languages. The accuracy of the word-based character model joint with a word-based model were significantly lower than a sentence-based character model. We conclude also from these results and comparing with results of the reimplementation of DQM that early integration of the word-based character model performs much better as late integration via Meta-BiLSTM for a word-based character model.