GCEK

Exploiting global context and external knowledge for distantly supervised relation extraction

Requirements

• python >= 3.7
• mxnet >= 1.5.1

Run Code

1. preprocess NYT data

   NYT 570K

   cd codes/data/NYT_data/NYT_522611/extract_cpp/
   unzip -d ./ NYT_570088.zip
   ./extract

   NYT 520K

   cd codes/data/NYT_data/NYT_570088/extract_cpp/
   unzip -d ./ NYT_522611.zip
   ./extract

2. generate train data and test data

   cd dataProcess
   python NYTData.py

3. train model

   cd codes

   train with cpu

   python main.py -n 50 --lib GCEK -m GCEK -p GCEK_520K -o momentum --data_version 520

   train with gpu

   python main.py -c 0 -n 50 --lib GCEK -m GCEK -p GCEK_520K -o momentum --data_version 520

Cite

Please cite as:

@article{GCEK,
title = {Exploiting global context and external knowledge for distantly supervised relation extraction},
journal = {Knowledge-Based Systems},
volume = {261},
pages = {110195},
year = {2023},
issn = {0950-7051},
doi = {https://doi.org/10.1016/j.knosys.2022.110195},
url = {https://www.sciencedirect.com/science/article/pii/S0950705122012916},
author = {Jianwei Gao and Huaiyu Wan and Youfang Lin},
}