Datasets:

---

Duplicated from  ff06b5/Intentbench

leqiyyy

/

Intentbench

Like 1

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
coverage_mode: string
execution_mode: string
local_path_redaction_passed: bool
overall_pass: bool
postcheck_steps: int64
raw_evidence_sha256: string
redacted_evidence_sha256: string
tool_images: struct<batfish: string, frr: string, kathara: string>
  child 0, batfish: string
  child 1, frr: string
  child 2, kathara: string
validation_sha256: string
validation_version: string
gold: null
input: null
scenario_contract: null
sample_kind: string
template_family: string
scenario_id: string
semantic_frame: string
domain: string
provenance_status: string
task_id: string
subtask: string
trajectory_id: string
lifecycle_stage: string
source_dataset: string
split_assignment_scope: string
split: string
sidecar_refs: list<item: string>
  child 0, item: string
source_assets: list<item: struct<artifact_sha256: string, dataset: string, role: string, sidecar_ref: string, sourc (... 70 chars omitted)
  child 0, item: struct<artifact_sha256: string, dataset: string, role: string, sidecar_ref: string, source_id: strin (... 58 chars omitted)
      child 0, artifact_sha256: string
      child 1, dataset: string
      child 2, role: string
      child 3, sidecar_ref: string
      child 4, source_id: string
      child 5, source_record_id: string
      child 6, source_record_sha256: string
global_leakage_group: string
provenance: struct<derivation_version: string, license: string, license_status: string, primary_artifact_sha256: (... 164 chars omitted)
  child 0, derivation_version: string
  child 1, license: string
  child 2, license_status: string
  child 3, primary_artifact_sha256: string
  child 4, primary_source_id: string
  child 5, primary_source_record_id: string
  child 6, primary_source_record_sha256: string
  child 7, primary_source_revision: string
  child 8, release_eligible: bool
to
{'domain': Value('string'), 'global_leakage_group': Value('string'), 'gold': Json(decode=True), 'input': Json(decode=True), 'lifecycle_stage': Value('string'), 'provenance': {'derivation_version': Value('string'), 'license': Value('string'), 'license_status': Value('string'), 'primary_artifact_sha256': Value('string'), 'primary_source_id': Value('string'), 'primary_source_record_id': Value('string'), 'primary_source_record_sha256': Value('string'), 'primary_source_revision': Value('string'), 'release_eligible': Value('bool')}, 'provenance_status': Value('string'), 'sample_kind': Value('string'), 'scenario_contract': Json(decode=True), 'scenario_id': Value('string'), 'semantic_frame': Value('string'), 'sidecar_refs': List(Value('string')), 'source_assets': List({'artifact_sha256': Value('string'), 'dataset': Value('string'), 'role': Value('string'), 'sidecar_ref': Value('string'), 'source_id': Value('string'), 'source_record_id': Value('string'), 'source_record_sha256': Value('string')}), 'source_dataset': Value('string'), 'split': Value('string'), 'split_assignment_scope': Value('string'), 'subtask': Value('string'), 'task_id': Value('string'), 'template_family': Value('string'), 'trajectory_id': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                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 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              coverage_mode: string
              execution_mode: string
              local_path_redaction_passed: bool
              overall_pass: bool
              postcheck_steps: int64
              raw_evidence_sha256: string
              redacted_evidence_sha256: string
              tool_images: struct<batfish: string, frr: string, kathara: string>
                child 0, batfish: string
                child 1, frr: string
                child 2, kathara: string
              validation_sha256: string
              validation_version: string
              gold: null
              input: null
              scenario_contract: null
              sample_kind: string
              template_family: string
              scenario_id: string
              semantic_frame: string
              domain: string
              provenance_status: string
              task_id: string
              subtask: string
              trajectory_id: string
              lifecycle_stage: string
              source_dataset: string
              split_assignment_scope: string
              split: string
              sidecar_refs: list<item: string>
                child 0, item: string
              source_assets: list<item: struct<artifact_sha256: string, dataset: string, role: string, sidecar_ref: string, sourc (... 70 chars omitted)
                child 0, item: struct<artifact_sha256: string, dataset: string, role: string, sidecar_ref: string, source_id: strin (... 58 chars omitted)
                    child 0, artifact_sha256: string
                    child 1, dataset: string
                    child 2, role: string
                    child 3, sidecar_ref: string
                    child 4, source_id: string
                    child 5, source_record_id: string
                    child 6, source_record_sha256: string
              global_leakage_group: string
              provenance: struct<derivation_version: string, license: string, license_status: string, primary_artifact_sha256: (... 164 chars omitted)
                child 0, derivation_version: string
                child 1, license: string
                child 2, license_status: string
                child 3, primary_artifact_sha256: string
                child 4, primary_source_id: string
                child 5, primary_source_record_id: string
                child 6, primary_source_record_sha256: string
                child 7, primary_source_revision: string
                child 8, release_eligible: bool
              to
              {'domain': Value('string'), 'global_leakage_group': Value('string'), 'gold': Json(decode=True), 'input': Json(decode=True), 'lifecycle_stage': Value('string'), 'provenance': {'derivation_version': Value('string'), 'license': Value('string'), 'license_status': Value('string'), 'primary_artifact_sha256': Value('string'), 'primary_source_id': Value('string'), 'primary_source_record_id': Value('string'), 'primary_source_record_sha256': Value('string'), 'primary_source_revision': Value('string'), 'release_eligible': Value('bool')}, 'provenance_status': Value('string'), 'sample_kind': Value('string'), 'scenario_contract': Json(decode=True), 'scenario_id': Value('string'), 'semantic_frame': Value('string'), 'sidecar_refs': List(Value('string')), 'source_assets': List({'artifact_sha256': Value('string'), 'dataset': Value('string'), 'role': Value('string'), 'sidecar_ref': Value('string'), 'source_id': Value('string'), 'source_record_id': Value('string'), 'source_record_sha256': Value('string')}), 'source_dataset': Value('string'), 'split': Value('string'), 'split_assignment_scope': Value('string'), 'subtask': Value('string'), 'task_id': Value('string'), 'template_family': Value('string'), 'trajectory_id': Value('string')}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1879, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset