CORE

Source code for CORE

Requirements

Pytorch and Numpy are needed to run the code.

 pip install -r requirements.txt

Data can be obtained from here.

Run CORE

To train CORE for different datasets and different embedding schemes, run:

 bash [Dataset Name]_[Embedding Model]_train.sh

We run all experiments with NVIDIA V100 GPU with 32GB memory. CUDA 10.1 or above needs to be installed.

We also provide code for SDType-Cond: SDType-Cond.py

Acknowledgement

We refer to the code of RotatE. Thanks for their contributions.

Citation

If you find the source codes useful, please consider citing our paper:

@article{ge2022core,
  title={CORE: A knowledge graph entity type prediction method via complex space regression and embedding},
  author={Ge, Xiou and Wang, Yun-Cheng and Wang, Bin and Kuo, CC Jay},
  journal={Pattern Recognition Letters},
  volume={157},
  pages={97--103},
  year={2022},
  publisher={Elsevier}
}