The codes to the paper "Discourse Representation Structure Parsing" ACL 2018.

The data used in the experiments are stored in folder data, the pretrained word embeddings could be got in https://drive.google.com/open?id=0B1VhP65vISjoZ3ppTnR3YXRMd1E, and then put it into the folder data

Currently, we do test for each epoch, because the evaluation is carried by external components

cd EncDecDRSparsing
mkdir output_dev # storing development outputs
mkdir output_tst # storing test outputs
mkdir output_model # storing models
python encdec.py 

Tree-like structure should be converted into Discourse Representation Graph (DRG) for evaluation by drs2tuple.py. Take output_tst/1.drs for example.

python drs2tuple.py data/test.drs > data/test.tuple
python drs2tuple.py output_tst/1.drs > output_tst/1.tuple
python D-match/d-match.py -f1 data/test.tuple output_tst/1.tuple -pr -r 100 -p 10

Note that D-match is implemented in https://github.com/RikVN