Text Generation from Knowledge Graphs with Graph Transformers

This repository contains the source code of our paper, Text Generation from Knowledge Graphs with Graph Transformers, which is accepted for publication at NAACL 2019.

Instructions

Basic Usage:

python3.6 train.py -save <DIR>

This repository is under construction! Check back soon for more details.

AGENDA Dataset

The AGENDA dataset is available in a user-friendly json format in data/unprocessed.tar.gz

Citation

If this work is useful in your research, please cite our paper.

@inproceedings{koncel2019text,
  title={{T}ext {G}eneration from {K}nowledge {G}raphs with {G}raph {T}ransformers},
  author={Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, Mirella Lapata, and Hannaneh Hajishirzi},
  booktitle={NAACL},
  year={2019}
}

References

1. Hochreiter, Sepp, and Jürgen Schmidhuber. "Long short-term memory." Neural computation 9.8 (1997): 1735-1780.