  In this work, we propose a novel constituency parsing scheme. The model
predicts a vector of real-valued scalars, named syntactic distances, for each
split position in the input sentence. The syntactic distances specify the order
in which the split points will be selected, recursively partitioning the input,
in a top-down fashion. Compared to traditional shift-reduce parsing schemes,
our approach is free from the potential problem of compounding errors, while
being faster and easier to parallelize. Our model achieves competitive
performance amongst single model, discriminative parsers in the PTB dataset and
outperforms previous models in the CTB dataset.
