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
Training:
python3.6 train.py -save <DIR>
Use --help for a list of all training options.
To generate, use
python3.6 generator.py -save <SAVED MODEL>
with the appropriate model flags used to train the model
To evaluate, run
python3.6 eval.py <GENERATED TEXTS> <GOLD TARGETS>
AGENDA Dataset
The AGENDA dataset is available in a user-friendly json format in /data/unprocessed.tar.gz Preprocessed data is also available in /data.
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}
}