This repo contains the code for a state-of-the-art discourse relation classifier, trained and tested on PDTB V2.
Here We implemented the Tree-LSTM and Tree-GRU models and enhanced them with pos-tag information. You can find more details in our paper at IJCNLP 2017: Tag-Enhanced Tree-Structured Neural Networks for Implicit Discourse Relation Classiﬁcation.
We trained and and tested our models on PDTB V2 dataset. You should download them and convert the PDTB into a "pipe" delimited file using the built-in tool in the dataset.
To run the program, you can use the following command for preprocessing the data, prepare the formatted dataset and train the models:
python main.py [--preprocess] [--prepare] [--train]
For detailed usage, run
python main.py -h to see the list of options.