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Code for "Text Generation from Knowledge Graphs with Graph Transformers"
| Date | Stars |
|---|---|
| 2026-07-31 | 525 |
| 2026-08-03 | 525 |
| 2026-08-06 | 525 |
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# 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](https://arxiv.org/abs/1904.02342), which is accepted for publication at [NAACL 2019](http://naacl2019.org/).
# 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}
}
```
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matched fp:3270a93b93f0c118, llm:Repository description: 'Code for "Text Generation from Knowledge Graphs with Graph Transformers"' (Python).
matched fp:3270a93b93f0c118, llm:Repository description: 'Code for "Text Generation from Knowledge Graphs with Graph Transformers"' (Python).
matched fp:3270a93b93f0c118, llm:Repository description: 'Code for "Text Generation from Knowledge Graphs with Graph Transformers"' (Python).