This is the implementation of my paper: SENet for Weakly-Supervised Relation Extraction (CSAI 2018)

Click here for pdf draft: paper_draft

Accepted link: []() // todo

How to train?

1. unzip zipfile in data/ (the dataset is too large that you'd better download from here: https://github.com/darrenyaoyao/ResCNN_RelationExtraction/tree/master/data )
2. in cmd:

   python3 train.py

and test result will be saved to temp/ in format of pkl file

How to eval?

python3 eval.py

How to plot and compare with other models?

you need to fill in the pkl file path in plot script, and run

cd plot/
python3 plot_compare_with_other_model.py
python3 metric.py

Model structure

Best result(epoch ~= 170)

Prerequisits

1. Tensorflow-gpu==1.4.0
2. sklearn, tflearn, nltk, numpy
3. Python3

Other models for RE and some helpful repos

PCNN + ATT

ResCNN-9

Linguistic_adversity

About me

Master candidate from PRIS, BUPT.

Email: liujiashu2333@qq.com