  Transition-based dependency parsers often need sequences of local shift and
reduce operations to produce certain attachments. Correct individual decisions
hence require global information about the sentence context and mistakes cause
error propagation. This paper proposes a novel transition system, arc-swift,
that enables direct attachments between tokens farther apart with a single
transition. This allows the parser to leverage lexical information more
directly in transition decisions. Hence, arc-swift can achieve significantly
better performance with a very small beam size. Our parsers reduce error by
3.7--7.6% relative to those using existing transition systems on the Penn
Treebank dependency parsing task and English Universal Dependencies.
