Abstract. Maltparser is a contemporary dependency parsing machine learningbased system that shows great accuracy. However 90% for Labelled Attachment Score (LAS) seems to be a de f...
In this paper, we propose a novel method for semi-supervised learning of nonprojective log-linear dependency parsers using directly expressed linguistic prior knowledge (e.g. a no...
We formulate the problem of nonprojective dependency parsing as a polynomial-sized integer linear program. Our formulation is able to handle non-local output features in an effici...
An effective procedure for automatically acquiring a new set of disambiguation rules for an existing deterministic parser on the basis of tagged text is presented. Performance of ...
Syntactic models should be descriptively adequate and parsable. A syntactic description is autonomous in the sense that it has certain explicitformal properties. Such a descriptio...