DeepAI
Log In Sign Up

GATE: Graph Attention Transformer Encoder for Cross-lingual Relation and Event Extraction

10/06/2020
by   Wasi Uddin Ahmad, et al.
0

Prevalent approaches in cross-lingual relation and event extraction use graph convolutional networks (GCNs) with universal dependency parses to learn language-agnostic representations such that models trained on one language can be applied to other languages. However, GCNs lack in modeling long-range dependencies or disconnected words in the dependency tree. To address this challenge, we propose to utilize the self-attention mechanism where we explicitly fuse structural information to learn the dependencies between words at different syntactic distances. We introduce GATE, a Graph Attention Transformer Encoder, and test its cross-lingual transferability on relation and event extraction tasks. We perform rigorous experiments on the widely used ACE05 dataset that includes three typologically different languages: English, Chinese, and Arabic. The evaluation results show that GATE outperforms three recently proposed methods by a large margin. Our detailed analysis reveals that due to the reliance on syntactic dependencies, GATE produces robust representations that facilitate transfer across languages.

READ FULL TEXT

page 1

page 2

page 3

page 4

03/24/2020

Cross-Lingual Adaptation Using Universal Dependencies

We describe a cross-lingual adaptation method based on syntactic parse t...
10/16/2020

Cross-Lingual Relation Extraction with Transformers

Relation extraction (RE) is one of the most important tasks in informati...
03/30/2018

Robust Cross-lingual Hypernymy Detection using Dependency Context

Cross-lingual Hypernymy Detection involves determining if a word in one ...
11/08/2019

Cross-Lingual Relevance Transfer for Document Retrieval

Recent work has shown the surprising ability of multi-lingual BERT to se...
11/01/2018

Near or Far, Wide Range Zero-Shot Cross-Lingual Dependency Parsing

Cross-lingual transfer is the major means toleverage knowledge from high...
04/30/2021

GTN-ED: Event Detection Using Graph Transformer Networks

Recent works show that the graph structure of sentences, generated from ...
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...