The following packages should be installed:
PyTorch
: >= 1.12.1Transformers
: >= 4.2
Please modify data/model-conf/data.ini
according to paths of your own dataset.
You can download the processed PTB-train, where incompatible instances are removed. The meaning of compatibility can be viewd in our paper.
Try the following commands to train second-order Joint2o model:
python src/parse.py -c data/model-conf/bert-ptb/joint2o-bi.ini -d 0
To make predictions:
python src/pred.py -d 0 -c data/model-conf/bert-ptb/joint2o-bi.ini \
--path exp/bert-e25-ptb/joint2o-bi-s1/model \
--data_con data/ptb/test.pid \
--data_dep data/ptb/test.conllx \
--pred exp/joint2o-bi-s1/test.pred \
--decode satta
If you have any questions, feel free to contact me via emails.
If you are interested in our work, please cite
@inproceedings{gu-etal-2024-high-order,
title = {High-order Joint Constituency and Dependency Parsing},
author = {Yanggan, Gu and
Yang, Hou and
Zhefeng, Wang and
Xinyu, Duan and
Zhenghua, Li},
booktitle = {Proceedings of LREC-COLING},
year = {2024},
address = {Torino, Italia},
publisher = {International Committee on Computational Linguistics}
}