Awesome
TITer
This is the data and coded for our EMNLP 2021 paper TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting
Qucik Start
Data preprocessing
This is not necessary, but can greatly shorten the experiment time.
python3 preprocess_data.py --data_dir data/ICEWS14
Dirichlet parameter estimation
If you use the reward shaping module, you need to do this step.
python3 mle_dirichlet.py --data_dir data/ICEWS14 --time_span 24
Train
you can run as following:
python3 main.py --data_path data/ICEWS14 --cuda --do_train --reward_shaping --time_span 24
Test
you can run as following:
python3 main.py --data_path data/ICEWS14 --cuda --do_test --IM --load_model_path xxxxx
Acknowledgments
model/dirichlet.py is from https://github.com/ericsuh/dirichlet
Cite
@inproceedings{Haohai2021TITer,
title={TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting},
author={Haohai Sun, Jialun Zhong, Yunpu Ma, Zhen Han, Kun He.},
booktitle={EMNLP},
year={2021}
}