Code for EACL 2021 paper : Attention-based Relational Graph Convolutional Network for Target-Oriented Opinion Words Extraction
Models and results can be found at our EACL 2021 paper https://www.aclweb.org/anthology/2021.eacl-main.170.pdf
- python==3.7.7
- numpy==1.19.4
- pandas==1.1.4
- torch==1.7.0
- torch-cluster==1.5.8
- torch-scatter==2.0.5
- torch-sparse==0.6.8
- torch-spline-conv==1.2.0
- torch-geometric==1.6.1
- tqdm==4.46.0
- fitlog==0.9.13
- spacy==2.3.4
- transformers==4.1.1
- prepare spacy model for dependency parse.
- we prepare en_core_web_sm-2.2.5.tar.gz at ./data/spacy_model, please unzip it.
- create folders ./models , ./log , ./logs in the root directory of this project.
- ./models is the folder where model store.
- ./log is the folder stored log recording train and valid process.
- ./logs is the folder stored logs which fitlog generate.
- prepare bert model.
- please download https://huggingface.co/bert-base-uncased
- Target-BiLSTM
- ARGCN
bash run.sh