Awesome
RE-TaMM
This is the implementation of Relation Extraction with Type-aware Map Memories of Word Dependencies at ACL 2021.
You can e-mail Yuanhe Tian at yhtian@uw.edu
, if you have any questions.
Citation
If you use or extend our work, please cite our paper at ACL 2021.
@article{chen2021relation,
title={Relation Extraction with Type-aware Map Memories of Word Dependencies},
author={Chen, Guimin and Tian, Yuanhe and Song, Yan and Wan, Xiang},
journal={Findings of the Association for Computational Linguistics: ACLIJCNLP},
year={2021}
}
Requirements
Our code works with the following environment.
python>=3.7
pytorch>=1.3
Dataset
To obtain the data, you can go to data
directory for details.
Downloading BERT and RE-TaMM
In our paper, we use BERT (paper) as the encoder.
For BERT, please download pre-trained BERT-Base and BERT-Large English from Google or from HuggingFace. If you download it from Google, you need to convert the model from TensorFlow version to PyTorch version.
For RE-TAMM, you can download the models we trained in our experiments from Google Drive.
Run on Sample Data
Run run_sample.sh
to train a model on the small sample data under the sample_data
directory.
Training and Testing
You can find the command lines to train and test models in run_train.sh
and run_test.sh
, respectively.
Here are some important parameters:
--do_train
: train the model.--do_eval
: test the model.
To-do List
- Regular maintenance.
You can leave comments in the Issues
section, if you want us to implement any functions.