We propose a simple yet accurate method for dependency parsing that treats parsing as tagging (PaT). That is, our approach addresses the parsing of dependency trees with a sequence model implemented with a bidirectional LSTM over BERT embeddings, where the {``}tag{''} to be predicted at each token position is the relative position of the corresponding head... (read more)

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