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Pytorch Version QA4IE Code (Journal Version)

Requirements

  • torch = 1.7.1
  • wandb

Pretrained Models

Download preprocessed data and pretrained models here.

Uncompress them in ./data and ./out, respectively.

Training & Evaluation Scripts

Training and evaluation scripts are provided in ./scripts. Note that you need to execute the dump_SS.sh script before training QA module, and execute the dump_QA.sh before training the AT module.

IE-setting Evaluation

Evaluate in IE-setting with different types of scorer:

  • mean: average probability of answer sequence
  • prod: product of answer sequence probabilities
  • AT: use the output of the AT module as the score

python3 eval_ie.py --scorer <mean|prod|AT>

Cite Us

@inproceedings{qiu2018qa4ie,
  title={QA4IE: A question answering based framework for information extraction},
  author={Qiu, Lin and Zhou, Hao and Qu, Yanru and Zhang, Weinan and Li, Suoheng and Rong, Shu and Ru, Dongyu and Qian, Lihua and Tu, Kewei and Yu, Yong},
  booktitle={International Semantic Web Conference},
  pages={198--216},
  year={2018},
  organization={Springer}
}

@article{qiu2020qa4ie,
  title={Qa4ie: A question answering based system for document-level general information extraction},
  author={Qiu, Lin and Ru, Dongyu and Long, Quanyu and Zhang, Weinan and Yu, Yong},
  journal={IEEE Access},
  volume={8},
  pages={29677--29689},
  year={2020},
  publisher={IEEE}
}