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- config_name: zho.dep.scidtb.conllu
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path: zho.dep.scidtb.conllu/validation-*
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path: zho.dep.scidtb.conllu/test-*
- config_name: zho.dep.scidtb.rels
data_files:
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path: zho.dep.scidtb.rels/validation-*
- split: test
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Disrpt is a multilingual, multi-framework unified discourse analysis benchmark.
It unifies discourse relation classification tasks (.rels) and discourse segmentation (.connlu) for many languages.
⚠️ This repo only contains the disrpt dataset when the underlying data is permissively licensed. Some datasets rely on corpora like the PTB.
To load these datasets, do the following:
pip install disrpt-utils
from disrpt_utils import load_dataset
corpora_paths={
#TODO Input your own paths
"tur.pdtb.tdb": "/mnt/nfs_share_magnet2/dsileo/data/disrpt/TDB1.0/raw/",
"eng.rst.rstdt": "/mnt/nfs_share_magnet2/dsileo/data/disrpt/RSTtrees-WSJ-main-1.0-20231128T125253Z-001/"
}
config_name="eng.rst.rstdt"
load_dataset(config_name,'conllu',corpora_paths=corpora_paths)
Otherwise, most datasets are directly accessible:
from huggingface import load_dataset
load_dataset(/multilingual-discourse-hub/disrpt/'','eng.dep.scidtb.rels')
Citations
@inproceedings{braud2024disrpt,
title={{DISRPT}: A Multilingual, Multi-domain, Cross-framework Benchmark for Discourse Processing},
author={Braud, Chloé and Zeldes, Amir and Rivière, Laura and Liu, Yang Janet and Muller, Philippe and Sileo, Damien and Aoyama, Tatsuya},
booktitle={Proceedings of LREC-COLING 2024},
year={2024}
}
Underline datasets:
https://huggingface.co/datasets/multilingual-discourse-hub/disrpt/raw/main/bibtex.json