Code for the AAAI-19 paper "A Deep Sequential Model for Discourse Parsing on Multi-Party Dialogues" (Shi and Huang, 2019)
this paper is now available on arXiv, and please kindly cite it:
@inproceedings{shi2019deep,
title={A Deep Sequential Model for Discourse Parsing on Multi-Party Dialogues},
author={Shi, Zhouxing and Huang, Minlie},
booktitle={AAAI},
year={2019}
}
- Python 3
We use the STAC corpus.
You may transform the original dataset into JSON files by:
python data_pre.py <input_dir> <output_json_file>
We also use 100-dimensional Glove word vectors.
python main.py {--[option1]=[value1] --[option2]=[value2] ... }
Available options can be found at the top of main.py
.
For example, to train the model with default settings:
python main.py --is_train