Grid Tagging Scheme for Aspect-oriented Fine-grained Opinion Extraction. Zhen Wu, Chengcan Ying, Fei Zhao, Zhifang Fan, Xinyu Dai, Rui Xia. In Findings of EMNLP, 2020.
Data format descriptions are here.
- pytorch=1.4.0
- python=3.6
For example, you can use the folowing command to fine-tune Bert on the OPE task (the pre-trained Bert model is saved in the folder "pretrained/"):
python main.py --task pair --mode train --dataset res14
The best model will be saved in the folder "savemodel/".
For example, you can use the folowing command to test Bert on the OPE task:
python main.py --task pair --mode test --dataset res14
Note: In our pre-experiments, a smaller batch size and learning rate can achieve better performance on certain datasets, while we use a general setting in our paper to save time instead of adopting grid search.
If you used the datasets or code, please cite our paper:
@inproceedings{wu-etal-2020-grid,
title = "Grid Tagging Scheme for Aspect-oriented Fine-grained Opinion Extraction",
author = "Wu, Zhen and
Ying, Chengcan and
Zhao, Fei and
Fan, Zhifang and
Dai, Xinyu and
Xia, Rui",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2020.findings-emnlp.234",
doi = "10.18653/v1/2020.findings-emnlp.234",
pages = "2576--2585",
}
[1]. Zhen Wu, Chengcan Ying, Fei Zhao, Zhifang Fan, Xinyu Dai, Rui Xia. Grid Tagging Scheme for Aspect-oriented Fine-grained Opinion Extraction. In Findings of EMNLP, 2020.
[2]. Zhifang Fan, Zhen Wu, Xin-Yu Dai, Shujian Huang, Jiajun Chen. Target-oriented Opinion Words Extraction with Target-fused Neural Sequence Labeling. In Proceedings of NAACL, 2019.