A* CCG Parsing with a Supertag and Dependency Factored Model

04/23/2017
by   Masashi Yoshikawa, et al.
0

We propose a new A* CCG parsing model in which the probability of a tree is decomposed into factors of CCG categories and its syntactic dependencies both defined on bi-directional LSTMs. Our factored model allows the precomputation of all probabilities and runs very efficiently, while modeling sentence structures explicitly via dependencies. Our model achieves the state-of-the-art results on English and Japanese CCG parsing.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/21/2016

Incremental Parsing with Minimal Features Using Bi-Directional LSTM

Recently, neural network approaches for parsing have largely automated t...
research
08/06/2016

Bi-directional Attention with Agreement for Dependency Parsing

We develop a novel bi-directional attention model for dependency parsing...
research
08/09/2015

An Automatic Machine Translation Evaluation Metric Based on Dependency Parsing Model

Most of the syntax-based metrics obtain the similarity by comparing the ...
research
01/04/2017

Neural Probabilistic Model for Non-projective MST Parsing

In this paper, we propose a probabilistic parsing model, which defines a...
research
06/11/2018

Straight to the Tree: Constituency Parsing with Neural Syntactic Distance

In this work, we propose a novel constituency parsing scheme. The model ...
research
08/28/2018

Unsupervised Learning of Syntactic Structure with Invertible Neural Projections

Unsupervised learning of syntactic structure is typically performed usin...
research
02/05/2020

Discontinuous Constituent Parsing with Pointer Networks

One of the most complex syntactic representations used in computational ...

Please sign up or login with your details

Forgot password? Click here to reset