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reranker-broad-policy-v1

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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
pair_id: string
query_id: string
query: string
text: string
label: double
relevance: double
candidate_id: string
candidate_kind: string
language: string
source: string
domain: string
candidates: list<item: struct<id: string, text: string, kind: string, relevance: double>>
  child 0, item: struct<id: string, text: string, kind: string, relevance: double>
      child 0, id: string
      child 1, text: string
      child 2, kind: string
      child 3, relevance: double
id: string
to
{'id': Value('string'), 'query': Value('string'), 'language': Value('string'), 'source': Value('string'), 'domain': Value('string'), 'candidates': List({'id': Value('string'), 'text': Value('string'), 'kind': Value('string'), 'relevance': Value('float64')})}
because column names don't match
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 2674, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2208, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2232, 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 483, 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 260, 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 120, 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 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              pair_id: string
              query_id: string
              query: string
              text: string
              label: double
              relevance: double
              candidate_id: string
              candidate_kind: string
              language: string
              source: string
              domain: string
              candidates: list<item: struct<id: string, text: string, kind: string, relevance: double>>
                child 0, item: struct<id: string, text: string, kind: string, relevance: double>
                    child 0, id: string
                    child 1, text: string
                    child 2, kind: string
                    child 3, relevance: double
              id: string
              to
              {'id': Value('string'), 'query': Value('string'), 'language': Value('string'), 'source': Value('string'), 'domain': Value('string'), 'candidates': List({'id': Value('string'), 'text': Value('string'), 'kind': Value('string'), 'relevance': Value('float64')})}
              because column names don't match

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Check out the documentation for more information.

Reranker Broad Policy V1

Synthetic judged reranker dataset for Irish-government-style search policy work.

Focus:

  • prefer relevant current service or guide pages for current-status queries
  • prefer target-year or latest relevant news for news-like or budget-like queries
  • weight the latest chat turn most heavily when queries contain newline-separated turns
  • use publication dates appended to titles when disambiguating near-duplicate news items

Files:

  • train.jsonl, valid.jsonl, test.jsonl: grouped reranker rows
  • train_pairs.jsonl, valid_pairs.jsonl: flattened pairwise rows
  • reranker_broad_policy_happy_v1.jsonl: straightforward policy cases
  • reranker_broad_policy_sad_v1.jsonl: confusable service-vs-news cases
  • reranker_broad_policy_redteam_v1.jsonl: adversarial latest-turn/date/year cases
  • reranker_broad_policy_all_v1.jsonl: union of all evaluation rows

This dataset is synthetic and policy-targeted. It is meant to complement broader judged reranker suites, not replace them.
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