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We propose the first multi-task learning model for joint Vietnamese wordsegmentation, part-of-speech (POS) tagging and dependency parsing. Inparticular, our model extends the BIST graph-based dependency parser(Kiperwasser and Goldberg, 2016) with BiLSTM-CRF-based neural layers (Huang etal., 2015) for word segmentation and POS tagging. On Vietnamese benchmarkdatasets, experimental results show that our joint model obtainsstate-of-the-art or competitive performances.

A neural joint model for Vietnamese word segmentation, POS tagging and dependency parsing