tianhaofu / x-gear Goto Github PK

Code for our ACL-2022 paper Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction.

• Python=3.7.10

$ conda env create -f environment.yml

• Go into the folder ./preprocessing/
• If you follow the instruction in the README.md, then you can get your data in the folder ./processed_data/

• Run ./scripts/generate_data_ace05.sh and ./scripts/generate_data_ere.sh to generate training examples of different languages for X-Gear. The generated training data will be saved in ./finetuned_data/.

• Run ./scripts/train_ace05.sh or ./scripts/train_ere.sh to train X-Gear. Alternatively, you can run the following command.

  python ./xgear/train.py -c ./config/config_ace05_mT5copy-base_en.json
  

  This trains X-Gear with mT5-base + copy mechanisim for ACE-05 English. The model will be saved in ./output/. You can modify the arguments in the config file or replace the config file with other files in ./config/.

• Run the following script to evaluate the performance for ACE-05 English, Arabic, and Chinese.

  ./scripts/eval_ace05.sh [model_path] [prediction_dir]
  

  If you want to test X-Gear with mT5-large, remember to modify the config file in ./scripts/eval_ace05.sh.

• Run the following script to evaluate the performance for ERE English and Spanish.

  ./scripts/eval_ere.sh [model_path] [prediction_dir]
  

  If you want to test X-Gear with mT5-large, remember to modify the config file in ./scripts/eval_ere.sh.

We provide our pre-trained models and show their performances as follows.

ACE-05

ERE

If you find that the code is useful in your research, please consider citing our paper.

@inproceedings{acl2022xgear,
    author    = {Kuan-Hao Huang and I-Hung Hsu and Premkumar Natarajan and Kai-Wei Chang and Nanyun Peng},
    title     = {Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction},
    booktitle = {Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL)},
    year      = {2022},
}