Awesome
This is the code for the paper A Simple But Powerful Graph Encoder for Temporal Knowledge Graph Completion accepted to NeurIPS 2022 Temporal Graph Learning Workshop paper
Preprocessing
If you want you run the demo on ICEWS14, ICEWS05-15 or GDELT, go to 'Software/dataset/${DATASET}'
, and run:
python preprocess.py
Then you can train on corresponding datasets.
Training
To run the training demo, please run:
python main.py --dataset ${DATASET}
Testing
To test a trained model, please run:
python main.py --dataset ${DATASET} --test --resume --name ${CHECKPOINT_NAME}
Generalization to unseen timestamps
Please go to 'Software/dataset/icews14_unseen'
and run:
python preprocess_extrapolate.py
Then go to the root directory and run:
python main.py --dataset icews14_unseen
Generalization to irregular timestamped data
Please run:
python main.py --dataset icews14_irr