DeepAI AI Chat
Log In Sign Up

ShanghaiTech at MRP 2019: Sequence-to-Graph Transduction with Second-Order Edge Inference for Cross-Framework Meaning Representation Parsing

04/08/2020
by   Xinyu Wang, et al.
0

This paper presents the system used in our submission to the CoNLL 2019 shared task: Cross-Framework Meaning Representation Parsing. Our system is a graph-based parser which combines an extended pointer-generator network that generates nodes and a second-order mean field variational inference module that predicts edges. Our system achieved 1 and 2 place for the DM and PSD frameworks respectively on the in-framework ranks and achieved 3 place for the DM framework on the cross-framework ranks.

READ FULL TEXT
06/19/2019

Second-Order Semantic Dependency Parsing with End-to-End Neural Networks

Semantic dependency parsing aims to identify semantic relationships betw...
10/12/2020

HUJI-KU at MRP 2020: Two Transition-based Neural Parsers

This paper describes the HUJI-KU system submission to the shared task on...
06/02/2020

Enhanced Universal Dependency Parsing with Second-Order Inference and Mixture of Training Data

This paper presents the system used in our submission to the IWPT 2020 S...
10/03/2019

Hitachi at MRP 2019: Unified Encoder-to-Biaffine Network for Cross-Framework Meaning Representation Parsing

This paper describes the proposed system of the Hitachi team for the Cro...
04/07/2022

Modeling Label Correlations for Second-Order Semantic Dependency Parsing with Mean-Field Inference

Second-order semantic parsing with end-to-end mean-field inference has b...
05/03/2020

Efficient Second-Order TreeCRF for Neural Dependency Parsing

In the deep learning (DL) era, parsing models are extremely simplified w...
11/16/2017

ConvAMR: Abstract meaning representation parsing for legal document

Convolutional neural networks (CNN) have recently achieved remarkable pe...