This repository includes the code of MTransE var4 (see paper), links to the data sets, and pretrained models.
Make sure your local environment has the following installed:
Python >= 2.7.6
pip
Install the dependents using:
./install.sh
Please first download the data sets:
http://yellowstone.cs.ucla.edu/~muhao/MTransE/data.zip
and pretrained models
http://yellowstone.cs.ucla.edu/~muhao/MTransE/models.zip
Unpack these two folders to the local clone of the repository.
To run the experiments on WK3l (wikipedia graphs), use:
./run_wk3l.sh
To run the experiments on CN3l (conceptNet), use:
./run_cn3l.sh
You may also train your own models on these two data sets using:
./train_models.sh
Please refer to our paper. Muhao Chen, Yingtao Tian, Mohan Yang, Carlo Zaniolo. Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017
@inproceedings{chen2017multigraph,
title={Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment},
author={Chen, Muhao and Tian, Yingtao and Yang, Mohan and Zaniolo, Carlo},
booktitle={Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI)},
year={2017}
}