SCR

Hi! This is the repository for the EMNLP 2023 oral paper: Continual Event Extraction with Semantic Confusion Rectification.

Requirements

Please make sure you have installed the packages in ./environment.yml.

Data Preprocessing

We use the ACE, ERE and MAVEN datasets for evaluation. Due to that the ACE and ERE datasets are not released publicly, we can't provide the dataset after processing. You can obtain the MAVEN datasets after processing through this link.

For ACE and ERE datasets, please first follow OneIE to process the dataset. Then you should process the data format to be like ./data/{DATASET_NAME}+/toy.json and name them "train.json", "valid.json", "test.json", respectively.

Pretrained Models

Download pretrained language model from huggingface and put it into the ./pertrain_model directory.

Training and Testing

You can train and test the SCR model with the following command:

sh run_{DATASET_NAME}.sh

You can modify the hyperparameter in ./config/{DATASET_NAME}.ini

Note that {DATASET_NAME} is one of the the dataset names include ace, ere and maven.

Citation

If you find our paper helpful, please cite the following paper. Thanks a lot!

@inproceedings{wang-etal-2023-continual,
    title = "Continual Event Extraction with Semantic Confusion Rectification",
    author = "Wang, Zitao  and Wang, Xinyi and Hu, Wei",
    booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
    year = "2023",
    address = "Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.emnlp-main.732",
    doi = "10.18653/v1/2023.emnlp-main.732",
    pages = "11945--11955",
}