Fill it up: Exploiting partial dependency annotations in a minimum spanning tree parser

26 Nov 2016 Liang Sun Jason Mielens Jason Baldridge

Unsupervised models of dependency parsing typically require large amounts of clean, unlabeled data plus gold-standard part-of-speech tags. Adding indirect supervision (e.g. language universals and rules) can help, but we show that obtaining small amounts of direct supervision - here, partial dependency annotations - provides a strong balance between zero and full supervision... (read more)

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