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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    ReadError
Message:      invalid header
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.9/tarfile.py", line 186, in nti
                  s = nts(s, "ascii", "strict")
                File "/usr/local/lib/python3.9/tarfile.py", line 170, in nts
                  return s.decode(encoding, errors)
              UnicodeDecodeError: 'ascii' codec can't decode byte 0xe3 in position 0: ordinal not in range(128)
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.9/tarfile.py", line 2336, in next
                  tarinfo = self.tarinfo.fromtarfile(self)
                File "/usr/local/lib/python3.9/tarfile.py", line 1122, in fromtarfile
                  obj = cls.frombuf(buf, tarfile.encoding, tarfile.errors)
                File "/usr/local/lib/python3.9/tarfile.py", line 1064, in frombuf
                  chksum = nti(buf[148:156])
                File "/usr/local/lib/python3.9/tarfile.py", line 189, in nti
                  raise InvalidHeaderError("invalid header")
              tarfile.InvalidHeaderError: invalid header
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 484, in compute_first_rows_response
                  rows = get_rows(
                File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 119, in decorator
                  return func(*args, **kwargs)
                File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 175, 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/iterable_dataset.py", line 747, in __iter__
                  for key, example in self._iter():
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 737, in _iter
                  yield from ex_iterable
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 106, in __iter__
                  yield from self.generate_examples_fn(**self.kwargs)
                File "/tmp/modules-cache/datasets_modules/datasets/biu-nlp--qanom/27e3b0a3f0e07958d29c445c53218f3dd9115cec2851e017fae990de6fe0ef09/qanom.py", line 249, in _generate_examples_from_jsonl
                  orig_splits_jsons = [read_lines(filepath)
                File "/tmp/modules-cache/datasets_modules/datasets/biu-nlp--qanom/27e3b0a3f0e07958d29c445c53218f3dd9115cec2851e017fae990de6fe0ef09/qanom.py", line 249, in <listcomp>
                  orig_splits_jsons = [read_lines(filepath)
                File "/tmp/modules-cache/datasets_modules/datasets/biu-nlp--qanom/27e3b0a3f0e07958d29c445c53218f3dd9115cec2851e017fae990de6fe0ef09/qanom.py", line 245, in read_lines
                  with gzip.open(filepath, "rt") as f:
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/streaming.py", line 69, 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/streaming_download_manager.py", line 702, in xgzip_open
                  return gzip.open(xopen(filepath_or_buffer, "rb", use_auth_token=use_auth_token), *args, **kwargs)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 469, in xopen
                  file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/core.py", line 441, in open
                  return open_files(
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/core.py", line 273, in open_files
                  fs, fs_token, paths = get_fs_token_paths(
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/core.py", line 606, in get_fs_token_paths
                  fs = filesystem(protocol, **inkwargs)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 284, in filesystem
                  return cls(**storage_options)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 76, in __call__
                  obj = super().__call__(*args, **kwargs)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/implementations/tar.py", line 86, in __init__
                  self.tar = tarfile.TarFile(fileobj=self.fo)
                File "/usr/local/lib/python3.9/tarfile.py", line 1531, in __init__
                  self.firstmember = self.next()
                File "/usr/local/lib/python3.9/tarfile.py", line 2348, in next
                  raise ReadError(str(e))
              tarfile.ReadError: invalid header

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QANom

This dataset contains question-answer pairs to model the predicate-argument structure of deverbal nominalizations. The questions start with wh-words (Who, What, Where, What, etc.) and contain the verbal form of a nominalization from the sentence; the answers are phrases in the sentence.

See the paper for details: QANom: Question-Answer driven SRL for Nominalizations (Klein et. al., COLING 2020)

For previewing the QANom data along with the verbal annotations of QASRL, check out https://browse.qasrl.org/. Also check out our GitHub repository to find code for nominalization identification, QANom annotation, evaluation, and models.

The dataset was annotated by selected workers from Amazon Mechanical Turk.

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