Sequential Graph Dependency Parser
Machine Learning
2019-10-25 v2 Computation and Language
Machine Learning
Abstract
We propose a method for non-projective dependency parsing by incrementally predicting a set of edges. Since the edges do not have a pre-specified order, we propose a set-based learning method. Our method blends graph, transition, and easy-first parsing, including a prior state of the parser as a special case. The proposed transition-based method successfully parses near the state of the art on both projective and non-projective languages, without assuming a certain parsing order.
Cite
@article{arxiv.1905.10930,
title = {Sequential Graph Dependency Parser},
author = {Sean Welleck and Kyunghyun Cho},
journal= {arXiv preprint arXiv:1905.10930},
year = {2019}
}
Comments
RANLP 2019