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/first_rows.py", line 537, in compute_first_rows_response
                  rows = get_rows(
                File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 144, in decorator
                  return func(*args, **kwargs)
                File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 188, in get_rows
                  ds = load_dataset(
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/load.py", 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/builder.py", line 1206, in as_streaming_dataset
                  splits_generators = {sg.name: sg for sg in self._split_generators(dl_manager)}
                File "/tmp/modules-cache/datasets_modules/datasets/universal_morphologies/4bafcfad1b98576ec4d22fe6c73b82cb9fee0ba690f5f62730b010abb4e70c43/universal_morphologies.py", line 452, in _split_generators
                  data_dir = dl_manager.download_and_extract(config_urls)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1074, in download_and_extract
                  return self.extract(self.download(url_or_urls))
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", 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/py_utils.py", line 444, in map_nested
                  mapped = [
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", 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/py_utils.py", line 346, in _single_map_nested
                  return function(data_struct)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", 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/streaming_download_manager.py", 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/streaming_download_manager.py", line 401, in _get_extraction_protocol_with_magic_number
                  f.seek(0)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 737, in seek
                  raise ValueError("Cannot seek streaming HTTP file")
              ValueError: Cannot seek streaming HTTP file

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Dataset Summary

The Universal Morphology (UniMorph) project is a collaborative effort to improve how NLP handles complex morphology in the world’s languages. The goal of UniMorph is to annotate morphological data in a universal schema that allows an inflected word from any language to be defined by its lexical meaning, typically carried by the lemma, and by a rendering of its inflectional form in terms of a bundle of morphological features from our schema. The specification of the schema is described in Sylak-Glassman (2016).

Supported Tasks and Leaderboards

[More Information Needed]

Languages

The current version of the UniMorph dataset covers 110 languages.

Dataset Structure

Data Instances

Each data instance comprises of a lemma and a set of possible realizations with morphological and meaning annotations. For example:

{'forms': {'Aktionsart': [[], [], [], [], []],
  'Animacy': [[], [], [], [], []],
  ...
  'Finiteness': [[], [], [], [1], []],
  ...
  'Number': [[], [], [0], [], []],
  'Other': [[], [], [], [], []],
  'Part_Of_Speech': [[7], [10], [7], [7], [10]],
  ...
  'Tense': [[1], [1], [0], [], [0]],
  ...
  'word': ['ablated', 'ablated', 'ablates', 'ablate', 'ablating']},
 'lemma': 'ablate'}

Data Fields

Each instance in the dataset has the following fields:

lemma: the common lemma for all all_forms
forms: all annotated forms for this lemma, with:
- word: the full word form
- [category]: a categorical variable denoting one or several tags in a category (several to represent composite tags, originally denoted with A+B). The full list of categories and possible tags for each can be found here

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

[More Information Needed]

Licensing Information

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Citation Information

[More Information Needed]

Contributions

Thanks to @yjernite for adding this dataset.

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