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Datasets:
HiTZ
/
latxa-corpus-v2

Tasks:
Fill-Mask
Text Generation
Modalities:
Text
Formats:
json
Sub-tasks:
language-modeling
masked-language-modeling
Languages:
Basque
Size:
1M - 10M
ArXiv:
Libraries:
Datasets
Dask
Dataset card Data Studio Files
xet
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Dataset Viewer (First 5GB)
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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'aldizkariak' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Column(/meta/year) changed from string to number in row 4
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 174, in _generate_tables
                  df = pandas_read_json(f)
                       ^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 815, in read_json
                  return json_reader.read()
                         ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1014, in read
                  obj = self._get_object_parser(self.data)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
                  obj = FrameParser(json, **kwargs).parse()
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1176, in parse
                  self._parse()
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1392, in _parse
                  ujson_loads(json, precise_float=self.precise_float), dtype=None
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
              ValueError: Trailing data
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
                  for key, example in iterator:
                                      ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 503, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 350, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 177, in _generate_tables
                  raise e
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 151, in _generate_tables
                  pa_table = paj.read_json(
                             ^^^^^^^^^^^^^^
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: JSON parse error: Column(/meta/year) changed from string to number in row 4

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Latxa Corpus v2

Dataset Summary

  • Curated by: HiTZ Research Center & IXA Research group (University of the Basque Country UPV/EHU)
  • Language(s): eu-ES

Latxa Corpus v2 is a large-scale monolingual Basque corpus, created by combining curated crawls, public datasets, institutional data, and newly collected resources. Compared to v1.1, it substantially increases coverage, diversity, and volume. The final corpus is deduplicated, filtered, and ready for language model pretraining.

Data Sources

Data Statistics

The size of each dataset in terms of number of documents can be found below:

Train Valid Test
Aldizkariak 3,260 33 33
BOG 169,665 1,731 1,731
Booktegi 175 1 1
BOPV 42,798 437 887
BOTHA 92,249 941 941
Colossal OSCAR 89,856 915 915
CulturaX 870,464 8,882 8,882
Egunkaria 174,776 1,783 1,783
Euscrawl v2 3,958,893 20,283 20,283
FinePDFs 277,572 2,803 837
FineWeb2 341,296 3,482 3,482
HPLT v1 894,590 9,128 9,128
HPLT v2 567,503 5,790 5,790
OpenSubs 870 8 8
ParlEus 22,818 231 560
Wikipedia 456,273 4,655 4,655
ZelaiHandi 189,975 1,938 1,938

Licensing

We do not claim ownership of any document in the corpus. Should you consider that our data contains material that is owned by you and you would not like to be reproduced here, please contact us at [email protected]. For detailed information regarding the licenses associated with each individual corpus and document comprising this training dataset, please refer to the "license" field within "meta" or the respective references listed alongside each corpus entry.

Funding

This work is funded by the Basque Government (IKER-GAITU project) and the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the project ILENIA with reference 2022/TL22/00215335 and within the framework of the project Desarrollo de Modelos ALIA.

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Size of the auto-converted Parquet files (First 5GB per split):
7.57 GB
Number of rows (First 5GB per split):
2,603,471
Estimated number of rows:
2,689,916