Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks

03/16/2021
by   Minh Van Nguyen, et al.
0

Existing works on information extraction (IE) have mainly solved the four main tasks separately (entity mention recognition, relation extraction, event trigger detection, and argument extraction), thus failing to benefit from inter-dependencies between tasks. This paper presents a novel deep learning model to simultaneously solve the four tasks of IE in a single model (called FourIE). Compared to few prior work on jointly performing four IE tasks, FourIE features two novel contributions to capture inter-dependencies between tasks. First, at the representation level, we introduce an interaction graph between instances of the four tasks that is used to enrich the prediction representation for one instance with those from related instances of other tasks. Second, at the label level, we propose a dependency graph for the information types in the four IE tasks that captures the connections between the types expressed in an input sentence. A new regularization mechanism is introduced to enforce the consistency between the golden and predicted type dependency graphs to improve representation learning. We show that the proposed model achieves the state-of-the-art performance for joint IE on both monolingual and multilingual learning settings with three different languages.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/11/2019

Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network

Inter-sentence relation extraction deals with a number of complex semant...
research
11/05/2019

A Joint Model for Definition Extraction with Syntactic Connection and Semantic Consistency

Definition Extraction (DE) is one of the well-known topics in Informatio...
research
12/17/2022

Joint Information Extraction with Cross-Task and Cross-Instance High-Order Modeling

Prior works on Information Extraction (IE) typically predict different t...
research
03/19/2020

Joint Event Extraction along Shortest Dependency Paths using Graph Convolutional Networks

Event extraction (EE) is one of the core information extraction tasks, w...
research
02/25/2020

Event Detection with Relation-Aware Graph Convolutional Neural Networks

Event detection (ED), a key subtask of information extraction, aims to r...
research
10/14/2021

A Simple, Strong and Robust Baseline for Distantly Supervised Relation Extraction

Distantly supervised relation extraction (DS-RE) is generally framed as ...
research
09/03/2018

End-to-End Argument Mining for Discussion Threads Based on Parallel Constrained Pointer Architecture

Argument Mining (AM) is a relatively recent discipline, which concentrat...

Please sign up or login with your details

Forgot password? Click here to reset