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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/workers/datasets_based/src/datasets_based/workers/", line 485, in compute_first_rows_response
                  rows = get_rows(
                File "/src/workers/datasets_based/src/datasets_based/workers/", line 120, in decorator
                  return func(*args, **kwargs)
                File "/src/workers/datasets_based/src/datasets_based/workers/", line 164, in get_rows
                  ds = load_dataset(
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/", line 1751, in load_dataset
                  return builder_instance.as_streaming_dataset(split=split)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/", line 1206, in as_streaming_dataset
                  splits_generators = { sg for sg in self._split_generators(dl_manager)}
                File "/tmp/modules-cache/datasets_modules/datasets/jfleg/ed4ab2367351fe31949f48849ae6732b164f0d5ea6bb5d4357ff4293ac89511b/", line 105, in _split_generators
                  downloaded_dev = dl_manager.download_and_extract(_URLs["dev"])
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/", line 1074, in download_and_extract
                  return self.extract(
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/", line 1026, in extract
                  urlpaths = map_nested(self._extract, url_or_urls, map_tuple=True)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/utils/", line 444, in map_nested
                  mapped = [
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/utils/", line 445, in <listcomp>
                  _single_map_nested((function, obj, types, None, True, None))
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/utils/", line 346, in _single_map_nested
                  return function(data_struct)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/", line 1031, in _extract
                  protocol = _get_extraction_protocol(urlpath, use_auth_token=self.download_config.use_auth_token)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/", line 434, in _get_extraction_protocol
                  return _get_extraction_protocol_with_magic_number(f)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/", line 401, in _get_extraction_protocol_with_magic_number
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/implementations/", line 737, in seek
                  raise ValueError("Cannot seek streaming HTTP file")
              ValueError: Cannot seek streaming HTTP file

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Dataset Card for JFLEG

Dataset Summary

JFLEG (JHU FLuency-Extended GUG) is an English grammatical error correction (GEC) corpus. It is a gold standard benchmark for developing and evaluating GEC systems with respect to fluency (extent to which a text is native-sounding) as well as grammaticality. For each source document, there are four human-written corrections.

Supported Tasks and Leaderboards

Grammatical error correction.


English (native as well as L2 writers)

Dataset Structure

Data Instances

Each instance contains a source sentence and four corrections. For example:

  'sentence': "They are moved by solar energy ."
  'corrections': [
    "They are moving by solar energy .",
    "They are moved by solar energy .",
    "They are moved by solar energy .",
    "They are propelled by solar energy ." 

Data Fields

  • sentence: original sentence written by an English learner
  • corrections: corrected versions by human annotators. The order of the annotations are consistent (eg first sentence will always be written by annotator "ref0").

Data Splits

  • This dataset contains 1511 examples in total and comprise a dev and test split.
  • There are 754 and 747 source sentences for dev and test, respectively.
  • Each sentence has 4 corresponding corrected versions.

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]


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

[More Information Needed]

Licensing Information

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Citation Information

This benchmark was proposed by Napoles et al., 2020.

  author    = {Napoles, Courtney  and  Sakaguchi, Keisuke  and  Tetreault, Joel},
  title     = {JFLEG: A Fluency Corpus and Benchmark for Grammatical Error Correction},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {229--234},
  url       = {}

  author    = {Heilman, Michael  and  Cahill, Aoife  and  Madnani, Nitin  and  Lopez, Melissa  and  Mulholland, Matthew  and  Tetreault, Joel},
  title     = {Predicting Grammaticality on an Ordinal Scale},
  booktitle = {Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  month     = {June},
  year      = {2014},
  address   = {Baltimore, Maryland},
  publisher = {Association for Computational Linguistics},
  pages     = {174--180},
  url       = {}


Thanks to @j-chim for adding this dataset.

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