EMNLP 2021: A Novel Global Feature-Oriented Relational Triple Extraction Model based on Table Filling.

Requirements

The main requirements are:

• python 3.6
• torch 1.7.0
• tqdm
• transformers 3.5.1
• bert4keras

Usage

• Get pre-trained BERT model Download BERT-BASE-CASED and put it under ./pretrained.

• Train and select the model

  python run.py --dataset=WebNLG  --train=train  --rounds=4
  python run.py --dataset=WebNLG_star   --train=train  --rounds=2
  python run.py --dataset=NYT24   --train=train  --rounds=3
  python run.py --dataset=NYT24_star   --train=train  --rounds=2
  python run.py --dataset=NYT29   --train=train  --rounds=3

• Evaluate on the test set

  python run.py --dataset=WebNLG  --train=test  --rounds=4
  python run.py --dataset=WebNLG_star   --train=test  --rounds=2
  python run.py --dataset=NYT24   --train=test  --rounds=3
  python run.py --dataset=NYT24_star   --train=test  --rounds=2
  python run.py --dataset=NYT29   --train=test  --rounds=3

Acknowledgement

Parts of our codes come from bert4keras.