This repository contains Pytorch implementation for "STAGE: Span Tagging and Greedy Inference Scheme for Aspect Sentiment Triplet Extraction" (AAAI 2023) (AAAI Version and Arxiv Version)
We conduct our experiments on Nvidia GeForce 3090 GPU, with CUDA version 11.6 and PyTorch v1.10.1.
To reproduce experimental environment.
conda create -n STAGE python=3.9
conda activate STAGE
python -m pip install -r requirements.txt
We use ASTE-Data-V2-EMNLP2020
from https://github.com/xuuuluuu/SemEval-Triplet-data.git
(widely-used datasets in ASTE task)
The data dir should be data/ASTE-Data-V2-EMNLP2020
(or , set the correct dataset_dir parameter during training or predicting)
To reproduce our best test
python run.py
Best logs/best_score.txt
when running on our environment.
We also provide our training log in logs/best_training.log
. Please ignore the time information as another tasks were also running at the same time.
Change model_path, dataset, version variants in ``predict.py'' and run:
python predict.py
We provide the output file logs/best_16res_3D_predict.log
Please kindly cite our paper if this paper and the code are helpful.
@article{Liang2023stage,
TITLE = {STAGE: Span Tagging and Greedy Inference Scheme for Aspect Sentiment Triplet Extraction},
VOLUME = {37},
URL = {https://ojs.aaai.org/index.php/AAAI/article/view/26547},
DOI = {10.1609/aaai.v37i11.26547},
NUMBER = {11},
JOURNAL = {Proceedings of the AAAI Conference on Artificial Intelligence},
AUTHOR = {Liang, Shuo
AND Wei, Wei
AND Mao, Xian-ling
AND Fu, Yuanyuan
AND Fang, Rui
AND Chen, Dangyang},
YEAR = {2023},
MONTH = {Jun.},
PAGES = {13174-13182}
}