This is the GitHub repo for our paper "P2: A Plan-and-Pretrain Approach for Knowledge Graph-to-Text Generation" by Qipeng Guo, Zhijing Jin, Ning Dai, Xipeng Qiu, Xiangyang Xue, David Wipf, and Zheng Zhang.
Our model achieves the top #1 performance at the English track of the WebNLG 2020 Challenge at INLG 2020 Workshop.
Our P2 model consists of two steps:
- Planner by relational graph convolutional networks (Zhao et al, 2020)
- Pretrained Seq2Seq model: T5 (Raffel et al., 2020)
Run the run.sh for the training and the fix_nonenglish.py is a post-process script to map the character back to the original non-english one.
Our model output on WebNLG 2020 test set is available at output.txt.
If you have any question, please feel free to email the first author, Qipeng Guo, by [email protected].
@article{guo2020p2,
title={P2: A Plan-and-Pretrain Approach for Knowledge Graph-to-Text Generation},
author={Qipeng Guo, Zhijing Jin, Ning Dai, Xipeng Qiu, Xiangyang Xue, David Wipf, and Zheng Zhang},
year={2017}
}