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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    NonStreamableDatasetError
Message:      Streaming is not possible for this dataset because data host server doesn't support HTTP range requests. You can still load this dataset in non-streaming mode by passing `streaming=False` (default)
Traceback:    Traceback (most recent call last):
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/", line 495, in xopen
                  file_obj =, mode=mode, *args, **kwargs).open()
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/", line 419, in open
                  return open_files(
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/", line 272, in open_files
                  fs, fs_token, paths = get_fs_token_paths(
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/", line 586, in get_fs_token_paths
                  fs = filesystem(protocol, **inkwargs)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/", line 252, in filesystem
                  return cls(**storage_options)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/", line 76, in __call__
                  obj = super().__call__(*args, **kwargs)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/implementations/", line 54, in __init__
         = zipfile.ZipFile(, mode=mode)
                File "/usr/local/lib/python3.9/", line 1266, in __init__
                File "/usr/local/lib/python3.9/", line 1329, in _RealGetContents
                  endrec = _EndRecData(fp)
                File "/usr/local/lib/python3.9/", line 263, in _EndRecData
        , 2)
                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
              The above exception was the direct cause of the following exception:
              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 176, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/", line 917, in __iter__
                  for key, example in ex_iterable:
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/", line 113, in __iter__
                  yield from self.generate_examples_fn(**self.kwargs)
                File "/tmp/modules-cache/datasets_modules/datasets/hybrid_qa/fabdc38783449dd6cb1acd25621af97b871e218fc3ab608191d492b408a93ab8/", line 144, in _generate_examples
                  with open(table_file_path, encoding="utf-8") as f:
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/", line 70, in wrapper
                  return function(*args, use_auth_token=use_auth_token, **kwargs)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/", line 498, in xopen
                  raise NonStreamableDatasetError(
     Streaming is not possible for this dataset because data host server doesn't support HTTP range requests. You can still load this dataset in non-streaming mode by passing `streaming=False` (default)

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Dataset Card for HybridQA

Dataset Summary

Existing question answering datasets focus on dealing with homogeneous information, based either only on text or KB/Table information alone. However, as human knowledge is distributed over heterogeneous forms, using homogeneous information alone might lead to severe coverage problems. To fill in the gap, we present HybridQA, a new large-scale question-answering dataset that requires reasoning on heterogeneous information. Each question is aligned with a Wikipedia table and multiple free-form corpora linked with the entities in the table. The questions are designed to aggregate both tabular information and text information, i.e., lack of either form would render the question unanswerable.

Supported Tasks and Leaderboards

[More Information Needed]


The dataset is in English language.

Dataset Structure

Data Instances

A typical example looks like this

    "question_id": "00009b9649d0dd0a",
    "question": "Who were the builders of the mosque in Herat with fire temples ?",
    "table_id": "List_of_mosques_in_Afghanistan_0",
    "answer_text": "Ghurids",
    "question_postag": "WP VBD DT NNS IN DT NN IN NNP IN NN NNS .",
    "table": {
        "url": "",
        "title": "List of mosques in Afghanistan",
        "header": [
        "data": [
                "value": "Kabul",
                "urls": [
                        "summary": "Kabul ( Persian : کابل , romanized : Kābol , Pashto : کابل , romanized : Kābəl ) is the capital and largest city of Afghanistan...",
                        "url": "/wiki/Kabul"
    "section_title": "",
    "section_text": "",
    "uid": "List_of_mosques_in_Afghanistan_0",
    "intro": "The following is an incomplete list of large mosques in Afghanistan:"

Data Fields

  • question_id (str)
  • question (str)
  • table_id (str)
  • answer_text (str)
  • question_postag (str)
  • table (dict):
    • url (str)
    • title (str)
    • header (list of str)
    • data (list of dict):
      • value (str)
      • urls (list of dict):
        • url (str)
        • summary (str)
  • section_title (str)
  • section_text (str)
  • uid (str)
  • intro (str)

Data Splits

The dataset is split into train, dev and test splits.

train validation test
N. Instances 62682 3466 3463

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

[More Information Needed]

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]


[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

[More Information Needed]

Citation Information

[More Information Needed]

  title={HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data},
  author={Chen, Wenhu and Zha, Hanwen and Chen, Zhiyu and Xiong, Wenhan and Wang, Hong and Wang, William},
  journal={Findings of EMNLP 2020},


Thanks to @patil-suraj for adding this dataset.

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