---
language:
- en
license: apache-2.0
dataset_info:
- config_name: eng.dep.scidtb.rels
  features:
  - name: doc
    dtype: string
  - name: unit1_toks
    dtype: string
  - name: unit2_toks
    dtype: string
  - name: unit1_txt
    dtype: string
  - name: unit2_txt
    dtype: string
  - name: s1_toks
    dtype: string
  - name: s2_toks
    dtype: string
  - name: unit1_sent
    dtype: string
  - name: unit2_sent
    dtype: string
  - name: dir
    dtype: string
  - name: orig_label
    dtype: string
  - name: label
    dtype: string
  splits:
  - name: train
    num_bytes: 3463826
    num_examples: 6060
  - name: validation
    num_bytes: 1125360
    num_examples: 1933
  - name: test
    num_bytes: 1092953
    num_examples: 1911
  download_size: 1494028
  dataset_size: 5682139
- config_name: zho.dep.scidtb.conllu
  features:
  - name: id
    sequence: string
  - name: form
    sequence: string
  - name: lemma
    sequence: string
  - name: upos
    sequence: string
  - name: xpos
    sequence: string
  - name: feats
    sequence: string
  - name: head
    sequence: string
  - name: deprel
    sequence: string
  - name: deps
    sequence: string
  - name: misc
    sequence: string
  - name: doc_id
    dtype: string
  - name: mwe
    sequence: 'null'
  splits:
  - name: train
    num_bytes: 827143
    num_examples: 308
  - name: validation
    num_bytes: 282227
    num_examples: 103
  - name: test
    num_bytes: 264697
    num_examples: 89
  download_size: 204388
  dataset_size: 1374067
- config_name: zho.dep.scidtb.rels
  features:
  - name: doc
    dtype: string
  - name: unit1_toks
    dtype: string
  - name: unit2_toks
    dtype: string
  - name: unit1_txt
    dtype: string
  - name: unit2_txt
    dtype: string
  - name: s1_toks
    dtype: string
  - name: s2_toks
    dtype: string
  - name: unit1_sent
    dtype: string
  - name: unit2_sent
    dtype: string
  - name: dir
    dtype: string
  - name: orig_label
    dtype: string
  - name: label
    dtype: string
  splits:
  - name: train
    num_bytes: 628861
    num_examples: 802
  - name: validation
    num_bytes: 228839
    num_examples: 281
  - name: test
    num_bytes: 181790
    num_examples: 215
  download_size: 254512
  dataset_size: 1039490
configs:
- config_name: eng.dep.scidtb.rels
  data_files:
  - split: train
    path: eng.dep.scidtb.rels/train-*
  - split: validation
    path: eng.dep.scidtb.rels/validation-*
  - split: test
    path: eng.dep.scidtb.rels/test-*
- config_name: zho.dep.scidtb.conllu
  data_files:
  - split: train
    path: zho.dep.scidtb.conllu/train-*
  - split: validation
    path: zho.dep.scidtb.conllu/validation-*
  - split: test
    path: zho.dep.scidtb.conllu/test-*
- config_name: zho.dep.scidtb.rels
  data_files:
  - split: train
    path: zho.dep.scidtb.rels/train-*
  - split: validation
    path: zho.dep.scidtb.rels/validation-*
  - split: test
    path: zho.dep.scidtb.rels/test-*
---
https://github.com/disrpt/sharedtask2023

scditb:
```
@inproceedings{yang-li-2018-scidtb,
    title = "{S}ci{DTB}: Discourse Dependency {T}ree{B}ank for Scientific Abstracts",
    author = "Yang, An  and
      Li, Sujian",
    booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
    month = jul,
    year = "2018",
    address = "Melbourne, Australia",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/P18-2071",
    doi = "10.18653/v1/P18-2071",
    pages = "444--449",
    abstract = "Annotation corpus for discourse relations benefits NLP tasks such as machine translation and question answering. In this paper, we present SciDTB, a domain-specific discourse treebank annotated on scientific articles. Different from widely-used RST-DT and PDTB, SciDTB uses dependency trees to represent discourse structure, which is flexible and simplified to some extent but do not sacrifice structural integrity. We discuss the labeling framework, annotation workflow and some statistics about SciDTB. Furthermore, our treebank is made as a benchmark for evaluating discourse dependency parsers, on which we provide several baselines as fundamental work.",
}
```