Tree Decomposition Attention for AMR-to-Text Generation
Implementation of the corresponding paper.
Credit: This code is based on the repo for the 2020 AAAI paper "Graph Transformer for Graph-to-Sequence Learning". We are grateful to the authors for open-sourcing their work.
Environment Setup
The code is tested with Python 3.6. All dependencies are listed in requirements.txt.
Data Preparation
The instructions to prepare AMR data are given in the generator_data folder.
Model Training and Evaluation
The following steps should be done in the generator folder. The default settings in this repo should reproduce the results in our paper. Please check all scripts for correct arguments before use.
- Preprocess data and train
sh prepare.sh # vocab and data preprocessing sh train.sh - Test and postprocess
sh work.sh # test sh test.sh # postprocess (make sure --output is set) - Evaluate
./multi-bleu.perl # BLEU eval python chrF++.py -H [hyp] -R [ref] # chrF++ eval java -Xmx2G -jar meteor-1.5.jar [hyp] [ref] -l en # Meteor eval