Edge-Linear First-Order Dependency Parsing with Undirected Minimum Spanning Tree Inference. (arXiv:1510.07482v1 [cs.CL])
The run time complexity of state-of-the-art inference algorithms in graph-based dependency parsing is super-linear in the number of input words (n). Recently, pruning algorithms for these models have shown to cut a large portion of the graph edges, with minimal damage to the resulting parse trees. Solving the inference problem in run time complexity determined solely by the number of edges (m) is hence of obvious importance.