In this project, we provide an end2end DRS parser where the EDU segmenter in "Zhang et al., Syntax-Guided Sequence to Sequence Modeling for Discourse Segmentation" and the DRS parser in "Zhang et al., Adversarial Learning for Discourse Rhetorical Structure Parsing" are applied.
Any questions, just send e-mails to zzlynx@outlook.com (Longyin Zhang).
Due to the file size limitation, we put the pre-trained model at https://pan.baidu.com/s/1u0FLgPydISKR-MVcs2SFdg, and the password is lynx. After obtaining the pre-trained models, you need to put the two files at the following two places. It should be noted that since many real-life data usually do not contain standard paragraph boundaries, we only provide the pre-trained model with sentence boundaries considered, which is closer to practical application.
(parser) data/models_saved/model.pth
(LM) data/models_saved/xl_model.pthPrepare your own data with reference to the examples in "data/e2e", where "raw.txt" refers to the article with several sentences, "edu.txt" refers to the texts after EDU segmentation, and "trees.pkl" refers to the generated DRS trees. When everything is ready, run the following command: (Highlight: you only need to prepare the raw.txt, others will be formed after you run pipeline.py)
python pipeline.py-- License
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