Year: 2015
Type: conference-paper
Abstract: Transition-based dependency parsers usually use transition systems that monotonically extend partial parse states until they identify a complete parse tree.Honnibal et al. (2013) showed that greedy onebest parsing accuracy can be improved by adding additional non-monotonic transitions that permit the parser to "repair" earlier parsing mistakes by "over-writing" earlier parsing decisions.This increases the size of the set of complete parse trees that each partial parse state can derive, enabling such a parser to escape the "garden paths" that can trap monotonic greedy transition-based dependency parsers.We describe a new set of non-monotonic transitions that permits a partial parse state to derive a larger set of completed parse trees than previous work, which allows our parser to escape from a larger set of garden paths.A parser with our new nonmonotonic transition system has 91.85% directed attachment accuracy, an improvement of 0.6% over a comparable parser using the standard monotonic arc-eager transitions.
DOI: 10.18653/v1/d15-1162
Authors: Matthew Honnibal, Mark Johnson
Institution: Macquarie University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2251329024