kg-reeval's Introduction

A Re-evaluation of Knowledge Graph Completion Methods

Source code for ACL 2020 paper on Knowledge Graph Evaluation

Overview

Effect of different evaluation protocols on recent KG embedding methods on FB15k-237 dataset. For TOP and BOTTOM, we report changes in performance with respect to RANDOM protocol. Please refer to paper for more details.

Dependencies

Compatible with TensorFlow 1.x, PyTorch 1.x, and Python 3.x.
Dependencies can be installed using requirements.txt.

Usage:

Codes for different models are included in their respective directories.
Run proproc.sh for unziping the data.

Citation:

Please cite the following paper if you use this code in your work.

@inproceedings{sun-etal-2020-evaluation,
    title = "A Re-evaluation of Knowledge Graph Completion Methods",
    author = "Sun, Zhiqing  and
      Vashishth, Shikhar  and
      Sanyal, Soumya  and
      Talukdar, Partha  and
      Yang, Yiming",
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.acl-main.489",
    doi = "10.18653/v1/2020.acl-main.489",
    pages = "5516--5522"
}