DEKG-ILP
May 6, 2022 ยท View on GitHub
The source code of Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction
Requirements
The required packages are listed in requirement.txt
The extended inductive link prediction experiments
All train and test data can be found in the data floder. Specifically, we train our model on train.txt in {dataset}_{version}. The main results are evaluated on the test.txt in {dataset}_{version}_mix, the results with enclosing links are evaluated on test.txtin {dataset}_{version}_enc, the results with bridging links are evaluated on test.txtin {dataset}_{version}_bri.
For example, to train the model DEKG-ILP on EQ of FB15k-237, run the following command:
python train.py -d FB15k-237_EQ -e DEKG-ILP_FB15k-237_EQ
To test DEKG-ILP, run the following commands:
# main result
python test_rank.py -d FB15k-237_EQ_mix -e DEKG-ILP_FB15k-237_EQ
# enclosing links only
python test_rank.py -d FB15k-237_EQ_enc -e DEKG-ILP_FB15k-237_EQ
# bridging links only
python test_rank.py -d FB15k-237_EQ_bri -e DEKG-ILP_FB15k-237_EQ
Acknowledgement
Our code refer to the code of Grail. Thanks for their contributions very much.