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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    TypeError
Message:      Couldn't cast array of type
struct<action_class: string, binding: string, interaction: string, kind: string, relationship_category: string>
to
{'embedded_payload_part_count': Value('int64'), 'kind': Value('string'), 'ole_object_relationship_count': Value('int64')}
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2303, in cast_table_to_schema
                  cast_array_to_feature(
                  ~~~~~~~~~~~~~~~~~~~~~^
                      table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                      feature,
                      ^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1852, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ~~~~^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2109, in cast_array_to_feature
                  casted_array_values = _c(array.values, feature.feature)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
                  return func(array, *args, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2149, in cast_array_to_feature
                  raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
              TypeError: Couldn't cast array of type
              struct<action_class: string, binding: string, interaction: string, kind: string, relationship_category: string>
              to
              {'embedded_payload_part_count': Value('int64'), 'kind': Value('string'), 'ole_object_relationship_count': Value('int64')}

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Presentation Change Assurance Benchmark (PCAB)

This is the dataset mirror for PCAB 0.2.0, an open, deterministic corpus for tools that review stored PowerPoint OOXML changes.

What is in the dataset

  • 12 paired baseline/candidate PresentationML packages.
  • One public, target-free truth.json per pair.
  • A root manifest.jsonl catalogue.

Every pair has fixed visible DrawingML text and exactly one changed ZIP member. The pairs cover click, hover, and mouse-over action changes; external hyperlink retargeting; macro, program, file, presentation, OLE-verb, media, navigation, and reserved actions; missing relationship bindings; opaque VBA-project bytes; and opaque embedded-object bytes.

The packages are synthetic and generated from source. They are not recovered business decks. example.invalid targets are non-routable. VBA and embedded members are inert marker bytes, not executable samples or real OLE documents.

Intended use

Use PCAB to evaluate a static presentation-diff, review gate, or analyzer:

  1. Inspect each baseline/candidate pair locally.
  2. Emit an observation report using the PCAB protocol.
  3. Score it with the accompanying pcab CLI.

The corpus records stored package facts only. It does not support claims about target reachability, macro validity or execution, OLE activation, media playback, PowerPoint rendering, trust decisions, exploitability, or runtime Office behavior.

Provenance and reproducibility

The canonical source, validator, scorer, checksums, and release assets are at SybilGambleyyu/presentation-change-benchmark. Run pcab validate --fixtures fixtures from the source checkout to verify archive integrity, deterministic generation, package-member boundaries, stable visible text, private action/relationship shape, and public truth without opening a presentation client or following any target.

The dataset is MIT licensed. Please cite the canonical GitHub release and pin the revision used in an evaluation.

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