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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.

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