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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    ValueError
Message:      Cannot seek streaming HTTP file
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/responses/first_rows.py", line 337, in get_first_rows_response
                  rows = get_rows(dataset, config, split, streaming=True, rows_max_number=rows_max_number, hf_token=hf_token)
                File "/src/services/worker/src/worker/utils.py", line 123, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/responses/first_rows.py", line 65, in get_rows
                  ds = load_dataset(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1739, in load_dataset
                  return builder_instance.as_streaming_dataset(split=split)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1025, in as_streaming_dataset
                  splits_generators = {sg.name: sg for sg in self._split_generators(dl_manager)}
                File "/tmp/modules-cache/datasets_modules/datasets/peer_read/3607edb68c7ce19098a4d9c9275079ccc4a33ab990f0ea01105374b46ba215dd/peer_read.py", line 211, in _split_generators
                  paths = self._get_paths(
                File "/tmp/modules-cache/datasets_modules/datasets/peer_read/3607edb68c7ce19098a4d9c9275079ccc4a33ab990f0ea01105374b46ba215dd/peer_read.py", line 71, in _get_paths
                  conference_paths = glob.glob(os.path.join(data_dir, "PeerRead-master/data/*"))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/streaming.py", line 67, in wrapper
                  return function(*args, use_auth_token=use_auth_token, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 522, in xglob
                  fs, *_ = fsspec.get_fs_token_paths(urlpath, storage_options=storage_options)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 606, in get_fs_token_paths
                  fs = filesystem(protocol, **inkwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 268, in filesystem
                  return cls(**storage_options)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 76, in __call__
                  obj = super().__call__(*args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 60, in __init__
                  self.zip = zipfile.ZipFile(self.fo, mode=mode)
                File "/usr/local/lib/python3.9/zipfile.py", line 1257, in __init__
                  self._RealGetContents()
                File "/usr/local/lib/python3.9/zipfile.py", line 1320, in _RealGetContents
                  endrec = _EndRecData(fp)
                File "/usr/local/lib/python3.9/zipfile.py", line 263, in _EndRecData
                  fpin.seek(0, 2)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 684, in seek
                  raise ValueError("Cannot seek streaming HTTP file")
              ValueError: Cannot seek streaming HTTP file

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Dataset Card for peer_read

Dataset Summary

PearRead is a dataset of scientific peer reviews available to help researchers study this important artifact. The dataset consists of over 14K paper drafts and the corresponding accept/reject decisions in top-tier venues including ACL, NIPS and ICLR, as well as over 10K textual peer reviews written by experts for a subset of the papers.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

en-English

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

parsed_pdfs

  • name: string Filename in the dataset
  • metadata: dict Paper metadata
    • source: string Paper source
    • authors: list<string> List of paper authors
    • title: string Paper title
    • sections: list<dict> List of section heading and corresponding description
      • heading: string Section heading
      • text: string Section description
    • references: string List of references
      • title: string Title of reference paper
      • author: list<string> List of reference paper authors
      • venue: string Reference venue
      • citeRegEx: string Reference citeRegEx
      • shortCiteRegEx: string Reference shortCiteRegEx
      • year: int Reference publish year
    • referenceMentions: list<string> List of reference mentions
      • referenceID: int Reference mention ID
      • context: string Reference mention context
      • startOffset: int Reference startOffset
      • endOffset: int Reference endOffset
    • year: int Paper publish year
    • abstractText: string Paper abstract
    • creator: string Paper creator

reviews

  • id: int Review ID
  • conference: string Conference name
  • comments: string Review comments
  • subjects: string Review subjects
  • version: string Review version
  • date_of_submission: string Submission date
  • title: string Paper title
  • authors: list<string> List of paper authors
  • accepted: bool Paper accepted flag
  • abstract: string Paper abstract
  • histories: list<string> Paper details with link
  • reviews: dict Paper reviews
    • date: string Date of review
    • title: string Paper title
    • other_keys: string Reviewer other details
    • originality: string Originality score
    • comments: string Reviewer comments
    • is_meta_review: bool Review type flag
    • recommendation: string Reviewer recommendation
    • replicability: string Replicability score
    • presentation_format: string Presentation type
    • clarity: string Clarity score
    • meaningful_comparison: string Meaningful comparison score
    • substance: string Substance score
    • reviewer_confidence: string Reviewer confidence score
    • soundness_correctness: string Soundness correctness score
    • appropriateness: string Appropriateness score
    • impact: string Impact score

Data Splits

[More Information Needed]

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

Dongyeop Kang, Waleed Ammar, Bhavana Dalvi Mishra, Madeleine van Zuylen, Sebastian Kohlmeier, Eduard Hovy, Roy Schwartz

Licensing Information

[More Information Needed]

Citation Information

@inproceedings{kang18naacl, title = {A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications}, author = {Dongyeop Kang and Waleed Ammar and Bhavana Dalvi and Madeleine van Zuylen and Sebastian Kohlmeier and Eduard Hovy and Roy Schwartz}, booktitle = {Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL)}, address = {New Orleans, USA}, month = {June}, url = {https://arxiv.org/abs/1804.09635}, year = {2018} }

Contributions

Thanks to @vinaykudari for adding this dataset.