English PTB

AbstractGraph based dependency parsing is inefficient when handling non-local features due to high computational complexity of inference. In this paper, we proposed an exact and efficient decoding algorithm based on …...

This work addresses the task of dependency labeling—assigning labels to an (unlabeled) dependency tree. We employ and extend a feature representation learning approach, op- timizing it for both high speed …...

AbstractSequence-to-sequence constituent parsing requires a linearization to represent trees as sequences. Top-down tree linearizations, which can be based on brackets or shift-reduce actions, have achieved the best accuracy to date. …...