This is the implementation of the DIRECT model from paper "Adjacency List Oriented Relational Fact Extraction via Adaptive Multi-task Learning".
- botocore==1.19.23
- numpy==1.18.5
- tqdm==4.49.0
- requests==2.24.0
- boto3==1.16.23
- torch==1.6.0+cu101
- tensorflow==2.3.1
-
Download google's pretrained model
bert-base-cased
for PyTorch from huggingface https://huggingface.co/bert-base-cased -
Download CasRel's data at: https://drive.google.com/drive/folders/1bZlGqjqf51IExb-ILFDq8iSEU6Nrv7qH
-
Run
data/partial/$data$/process.ipynb
to convert the format of data. -
Run
./train_$data$.sh
to train the model. -
RUn
./eval.sh
to eval.
@inproceedings{Zhao2021AdjacencyLO,
title={Adjacency List Oriented Relational Fact Extraction via Adaptive Multi-task Learning},
author={Fubang Zhao and Zhuoren Jiang and Yangyang Kang and Changlong Sun and Xiaozhong Liu},
year={2021}
}