Datasets:

---

xuzishan

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ib-attribution-160

like 0

Error code:   DatasetGenerationError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
task_id: string
name: string
prompt: string
gold: string
opus: struct<sc: double, exit: string, iters: int64, crit: list<item: struct<c: string, m: bool, e: string>>, ans: string, traj: list<item: struct<r: string, c: string, tc: list<item: struct<n: string, a: string>>>>>
hy: struct<sc: double, exit: string, iters: int64, crit: list<item: struct<c: string, m: bool, e: string>>, ans: string, traj: list<item: struct<r: string, c: string, tc: list<item: struct<n: string, a: string>>>>>
vs
task_id: string
opus: struct<verdict: string, pivotal_steps: list<item: struct<is_error_step: bool, location: string, step_or_iter: string, tool_call: string, action: string, observed_value: string, expected_value: string, step_type: string, downstream_effect: string>>, why: struct<key_decision: string, reason_correct_or_wrong: string, evidence: list<item: struct<source_type: string, step_or_iter: string, quote_or_value: string, supports: string>>>>
hy: struct<verdict: string, pivotal_steps: list<item: struct<is_error_step: bool, location: string, step_or_iter: string, tool_call: string, action: string, observed_value: string, expected_value: string, step_type: string, downstream_effect: string>>, why: struct<key_decision: string, reason_correct_or_wrong: string, evidence: list<item: struct<source_type: string, step_or_iter: string, quote_or_value: string, supports: string>>>>
divergence_step_pair: struct<opus_step: string, hy_step: string, diverged_on: string, one_line_diff: string, causal_strength: string, why_causal: string>
primary_score_affecting_categories: list<item: string>
secondary_score_affecting_categories: list<item: null>
non_score_affecting_process_issues: list<item: string>
failure_location_class: string
rubric_quality_check: struct<status: string, discrepancy_type: string, should_exclude_from_hy_failure: bool>
counterfactual: struct<applicable: bool, target: string, minimal_fix_action: string, fix_level: string, would_recover_score: string, prompt_rule_candidate: string>
confidence_per_field: struct<pivotal_steps: string, divergence: string, category: string, counterfactual: string, rubric_quality: string>
attribution_summary: string
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1858, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                                            ~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 781, in finalize
                  self.write_rows_on_file()
                  ~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 662, in write_rows_on_file
                  table = pa.concat_tables(self.current_rows)
                File "pyarrow/table.pxi", line 6320, in pyarrow.lib.concat_tables
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              task_id: string
              name: string
              prompt: string
              gold: string
              opus: struct<sc: double, exit: string, iters: int64, crit: list<item: struct<c: string, m: bool, e: string>>, ans: string, traj: list<item: struct<r: string, c: string, tc: list<item: struct<n: string, a: string>>>>>
              hy: struct<sc: double, exit: string, iters: int64, crit: list<item: struct<c: string, m: bool, e: string>>, ans: string, traj: list<item: struct<r: string, c: string, tc: list<item: struct<n: string, a: string>>>>>
              vs
              task_id: string
              opus: struct<verdict: string, pivotal_steps: list<item: struct<is_error_step: bool, location: string, step_or_iter: string, tool_call: string, action: string, observed_value: string, expected_value: string, step_type: string, downstream_effect: string>>, why: struct<key_decision: string, reason_correct_or_wrong: string, evidence: list<item: struct<source_type: string, step_or_iter: string, quote_or_value: string, supports: string>>>>
              hy: struct<verdict: string, pivotal_steps: list<item: struct<is_error_step: bool, location: string, step_or_iter: string, tool_call: string, action: string, observed_value: string, expected_value: string, step_type: string, downstream_effect: string>>, why: struct<key_decision: string, reason_correct_or_wrong: string, evidence: list<item: struct<source_type: string, step_or_iter: string, quote_or_value: string, supports: string>>>>
              divergence_step_pair: struct<opus_step: string, hy_step: string, diverged_on: string, one_line_diff: string, causal_strength: string, why_causal: string>
              primary_score_affecting_categories: list<item: string>
              secondary_score_affecting_categories: list<item: null>
              non_score_affecting_process_issues: list<item: string>
              failure_location_class: string
              rubric_quality_check: struct<status: string, discrepancy_type: string, should_exclude_from_hy_failure: bool>
              counterfactual: struct<applicable: bool, target: string, minimal_fix_action: string, fix_level: string, would_recover_score: string, prompt_rule_candidate: string>
              confidence_per_field: struct<pivotal_steps: string, divergence: string, category: string, counterfactual: string, rubric_quality: string>
              attribution_summary: string
              
              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 1683, 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 1869, 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