A Dynamic Oracle for Linear-Time 2-Planar Dependency Parsing

We propose an efficient dynamic oracle for training the 2-Planar transition-based parser, a linear-time parser with over 99 non-projective syntactic corpora. This novel approach outperforms the static training strategy in the vast majority of languages tested and scored better on most datasets than the arc-hybrid parser enhanced with the SWAP transition, which can handle unrestricted non-projectivity.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/20/2019

Global Greedy Dependency Parsing

Most syntactic dependency parsing models may fall into one of two catego...
research
06/11/2017

A Full Non-Monotonic Transition System for Unrestricted Non-Projective Parsing

Restricted non-monotonicity has been shown beneficial for the projective...
research
06/08/2018

Policy Gradient as a Proxy for Dynamic Oracles in Constituency Parsing

Dynamic oracles provide strong supervision for training constituency par...
research
10/08/2018

An AMR Aligner Tuned by Transition-based Parser

In this paper, we propose a new rich resource enhanced AMR aligner which...
research
11/28/2017

Hybrid Oracle: Making Use of Ambiguity in Transition-based Chinese Dependency Parsing

In the training of transition-based dependency parsers, an oracle is use...
research
04/01/2019

Discontinuous Constituency Parsing with a Stack-Free Transition System and a Dynamic Oracle

We introduce a novel transition system for discontinuous constituency pa...
research
04/21/2018

Faster Shift-Reduce Constituent Parsing with a Non-Binary, Bottom-Up Strategy

We propose a novel non-binary shift-reduce algorithm for constituent par...

Please sign up or login with your details

Forgot password? Click here to reset