Datasets:
Tasks:
Image-to-Text
Modalities:
Geospatial
Sub-tasks:
visual-question-answering
Languages:
English
Size:
n<1K
License:
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: ArrowInvalid
Message: Failed to parse string: '2018-11-14T18:42:58.000Z' as a scalar of type timestamp[s]: expected no zone offset.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
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 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, 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 295, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2281, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2233, in cast_table_to_schema
cast_array_to_feature(
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1804, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2011, in cast_array_to_feature
_c(array.field(name) if name in array_fields else null_array, subfeature)
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1806, in wrapper
return func(array, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2095, in cast_array_to_feature
return array_cast(
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1806, in wrapper
return func(array, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1958, in array_cast
return array.cast(pa_type)
^^^^^^^^^^^^^^^^^^^
File "pyarrow/array.pxi", line 1135, in pyarrow.lib.Array.cast
File "/usr/local/lib/python3.12/site-packages/pyarrow/compute.py", line 412, in cast
return call_function("cast", [arr], options, memory_pool)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "pyarrow/_compute.pyx", line 604, in pyarrow._compute.call_function
File "pyarrow/_compute.pyx", line 399, in pyarrow._compute.Function.call
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: Failed to parse string: '2018-11-14T18:42:58.000Z' as a scalar of type timestamp[s]: expected no zone offset.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Blackline Atlas Civilian Disruption Benchmark Seeds
Small public benchmark slices for structured civilian disruption triage.
Purpose:
- compare prompt baselines and small VLMs on the same runnable public slices
- regression-check structured JSON behavior before and after Blackline adaptation
- provide a public-facing benchmark artifact without exposing the internal gold set
Included slices:
internal_public_seed_v0: Blackline internal public seed (Blackline Atlas),1rowsxbd_public_seed_v0: xBD public seed (xBD / xView2),4rowsspacenet8_public_seed_v0: SpaceNet 8 public seed (SpaceNet 8),4rows
What this repo is:
- public benchmark-only seed material
- canonical
blackline_candidate_eval.jsonlrows plus copied image pairs - external transfer checks for disaster and flood disruption
What this repo is not:
- not the internal Blackline training corpus
- not the frozen Blackline gold eval set
- not a live conflict feed or operational monitoring service
Layout:
<slice_id>/blackline_candidate_eval.jsonl: canonical runnable benchmark rows<slice_id>/images/...: image pairs used by the slice<slice_id>/source_labels/...: public provenance files when available
Intended use:
- benchmark and demo material
- cross-model comparison on a shared public slice basket
- public reproducibility for a narrow part of the evaluation stack
Limitations:
- intentionally small seed slices
- external-only coverage, not full civilian lifeline taxonomy coverage
- mixed-source public artifacts; source terms apply per slice
- not a replacement for the full internal Blackline evaluation program
Licensing and provenance:
- each slice keeps its original public provenance files when available
- source terms and restrictions follow the original datasets and published artifacts referenced per slice
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