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shavarani
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SHINRA-5LDS

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train

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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.

Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Invalid value. in row 0
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 145, in _generate_tables
                  dataset = json.load(f)
                File "/usr/local/lib/python3.9/json/__init__.py", line 293, in load
                  return loads(fp.read(),
                File "/usr/local/lib/python3.9/json/__init__.py", line 346, in loads
                  return _default_decoder.decode(s)
                File "/usr/local/lib/python3.9/json/decoder.py", line 337, in decode
                  obj, end = self.raw_decode(s, idx=_w(s, 0).end())
                File "/usr/local/lib/python3.9/json/decoder.py", line 355, in raw_decode
                  raise JSONDecodeError("Expecting value", s, err.value) from None
              json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
              
              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 240, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2216, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1239, in _head
                  return _examples_to_batch(list(self.take(n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1389, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1044, in __iter__
                  yield from islice(self.ex_iterable, self.n)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 282, in __iter__
                  for key, pa_table in self.generate_tables_fn(**self.kwargs):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 148, in _generate_tables
                  raise e
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 122, in _generate_tables
                  pa_table = paj.read_json(
                File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0

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YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

This dataset was originally created in August 2018 and was published in Multi-class Multilingual Classification of Wikipedia Articles Using Extended Named Entity Tag Set in LREC'20 (https://huggingface.co/papers/1909.06502).

Description of the data files

enes.json: This file contains the annotation classes originally provided in the 'Extended Named Entity Hierarchy'. You can find more information about this in the 'Extended Named Entity Hierarchy' (http://www.lrec-conf.org/proceedings/lrec2002/pdf/120.pdf)
entity_annotations.json: This file includes hand annotations for Japanese Wikipedia pages along with Wikipedia page IDs of equivalent pages in English, French, German, and Farsi Wikipedia (wherever an equivalent page has been available).
data.jsonl: This standalone JSONL format file combines the information from enes.json and entity_annotations.json with downloaded Wikipedia articles. The articles were downloaded from Wikipedia during the last week of April 2024.
example_data_reader.py: This Python script provides an example data reader aimed at expediting the process of parsing and utilizing the data files.

If you have any questions or need assistance, feel free to reach out to Hassan S. Shavarani (sshavara@sfu.ca).

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