  Shi, Huang, and Lee (2017) obtained state-of-the-art results for English and
Chinese dependency parsing by combining dynamic-programming implementations of
transition-based dependency parsers with a minimal set of bidirectional LSTM
features. However, their results were limited to projective parsing. In this
paper, we extend their approach to support non-projectivity by providing the
first practical implementation of the MH_4 algorithm, an $O(n^4)$ mildly
nonprojective dynamic-programming parser with very high coverage on
non-projective treebanks. To make MH_4 compatible with minimal transition-based
feature sets, we introduce a transition-based interpretation of it in which
parser items are mapped to sequences of transitions. We thus obtain the first
implementation of global decoding for non-projective transition-based parsing,
and demonstrate empirically that it is more effective than its projective
counterpart in parsing a number of highly non-projective languages
