RIFRE

Pytorch implementation for codes in Representation Iterative Fusion Based on Heterogeneous Graph Neural Network for Joint Entity and Relation Extraction

Model

requirements

python 3.7
torch 1.3
tqdm
transformers
numpy

Clone and load BERT pretrained models

git clone https://github.com/zhao9797/RIFRE.git
mkdir RIFRE/datasets/bert
cd RIFRE/datasets/bert
sudo apt-get install git-lfs

## provide path of pretrained models
git clone https://huggingface.co/bert-base-cased
git clone https://huggingface.co/bert-base-uncased

cd bert-base-cased
git lfs pull
cd ..
cd bert-base-uncased
git lfs pull

Run the Code

python train.py

Citation

@article{ZHAO2021106888,
title = {Representation iterative fusion based on heterogeneous graph neural network for joint entity and relation extraction},
journal = {Knowledge-Based Systems},
pages = {106888},
year = {2021},
issn = {0950-7051},
doi = {https://doi.org/10.1016/j.knosys.2021.106888},
url = {https://www.sciencedirect.com/science/article/pii/S0950705121001519},
author = {Kang Zhao and Hua Xu and Yue Cheng and Xiaoteng Li and Kai Gao}
}