git《Joint Entity and Relation Extraction with Set Prediction Networks》(2020) GitHub:

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Overview

Joint Entity and Relation Extraction with Set Prediction Networks

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Source code for Joint Entity and Relation Extraction with Set Prediction Networks. We would appreciate it if you cite our paper as following:

@article{sui2020joint,
  title={Joint Entity and Relation Extraction with Set Prediction Networks},
  author={Sui, Dianbo and Chen, Yubo and Liu, Kang and Zhao, Jun and Zeng, Xiangrong and Liu, Shengping},
  journal={arXiv preprint arXiv:2011.01675},
  year={2020}
}

Model Training

NYT Partial Match

python -m main --num_generated_triplets 15 --na_rel_coef 1 --max_grad_norm 1 --max_epoch 100 --max_span_length 10

NYT Exact Match

python -m main --num_generated_triplets 15 --max_grad_norm 2.5 --na_rel_coef 0.25 --max_epoch 100 --max_span_length 10

or

python -m main --num_generated_triplets 15 --max_grad_norm 1 --na_rel_coef 0.5 --max_epoch 100 --max_span_length 10

WebNLG Partial Match

python -m main --batch_size 4 --num_generated_triplets 10 --na_rel_coef 0.25 --max_grad_norm 20  --max_epoch 100 --encoder_lr 0.00002 --decoder_lr 0.00005 --num_decoder_layers 4 --max_span_length 10 --weight_decay 0.000001 --lr_decay 0.02

Trained Model Parameters

Model parameters can be download in Baidu Pan (key: SetP) 😎

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