Awesome
Intra-Bag and Inter-Bag Attentions
Dependencies
The code is written in Python 3.6 and pytorch 0.3.0.
Evaluation Results
precision/recall curves
Precion/recall curves of CNN+ATT_BL, CNN+ATT_BL+BAG_ATT, CNN+ATT_RA, CNN+ATT RA+BAG ATT
<p align="center"><img width="40%" src="figure/CNNmethods.jpg"/></p>Precion/recall curves of PCNN+ATT_BL, PCNN+ATT_BL+BAG_ATT, PCNN+ATT_RA, PCNN+ATT_RA+BAG_ATT
<p align="center"><img width="40%" src="figure/PCNNmethods.jpg"/></p>AUC Results
Model | no BAG_ATT | BAG_ATT |
---|---|---|
CNN+ATT_BL | 0.376 | 0.388 |
CNN+ATT_RA | 0.398 | 0.407 |
PCNN+ATT_BL | 0.388 | 0.403 |
PCNN+ATT_RA | 0.403 | 0.422 |
Usage
-
upzip the file
NYT_data/NYT_data.zip
-
make data folder in the following structure
Intra-Bag-and-Inter-Bag-Attentions
|-- figure
|-- CNNmethods.pdf
|-- PCNNmethods.pdf
|-- model
|-- embedding.py
|-- model_bagatt.py
|-- pcnn.py
|-- NYT_data
|-- relation2id.txt
|-- test.txt
|-- train.txt
|-- vec.bin
|-- preprocess
|-- data2pkl.py
|-- extract.cpp
|-- pickledata.py
|-- preprocess.sh
|-- plot.py
|-- README.md
|-- train.py
- preprocess NYT data
cd preprocess; bash preprocess.sh; cd ..
- train model
CUDA_VISIBLE_DEVICES=0 python train.py --pretrain --use_RA --sent_encoding pcnn --modelname PCNN_ATTRA
- plot the precision/recall curve
python plot.py --model_name PCNN_ATTRA_BAGATT
Cite
If you use the code, please cite the following paper: "Distant Supervision Relation Extraction with Intra-Bag and Inter-Bag Attentions" Zhi-Xiu Ye, Zhen-Hua Ling. NAACL (2019)
@inproceedings{ye-ling-2019-distant,
title = "Distant Supervision Relation Extraction with Intra-Bag and Inter-Bag Attentions",
author = "Ye, Zhi-Xiu and
Ling, Zhen-Hua",
booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/N19-1288",
pages = "2810--2819",
}