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bcv-commons
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cross-lingual-span-profile

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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
grc:1: double
grc:10: double
grc:100: double
grc:1000: double
grc:1001: double
grc:1003: double
grc:1004: double
grc:1005: double
grc:1006: double
grc:1007: double
grc:1008: double
grc:1009: double
grc:101: double
grc:1010: double
grc:1011: double
grc:1012: double
grc:1013: double
grc:1014: double
grc:1015: double
grc:1016: double
grc:1017: double
grc:1018: double
grc:1019: double
grc:102: double
grc:1020: double
grc:1021: double
grc:1022: double
grc:1023: double
grc:1024: double
grc:1025: double
grc:1026: double
grc:1027: double
grc:1028: double
grc:1029: double
grc:103: double
grc:1030: double
grc:1031: double
grc:1032: double
grc:1033: double
grc:1034: double
grc:1035: double
grc:1036: double
grc:1037: double
grc:1038: double
grc:1039: double
grc:1040: double
grc:1041: double
grc:1042: double
grc:1043: double
grc:1044: double
grc:1045: double
grc:1046: double
grc:1047: double
grc:1048: double
grc:1049: double
grc:105: double
grc:1050: double
grc:1051: double
grc:1052: double
grc:1053: double
grc:1054: double
grc:1055: double
grc:1056: double
grc:1057: double
grc:1058: double
grc:1059: double
grc:106: double
grc:1060: double
grc:1061: double
grc:1062: double
grc:1064: double
grc:1066: double
grc:1067: double
grc:1068: double
grc:1069: double
grc:107: double
grc:1070: double
grc:1071: double
grc:1072: double
grc:1073: double
grc:1074: double
grc:1075: double
grc:1076: double
grc:1077: double
grc:1078: double
grc:1079: double
grc:108: double
grc:1080: double
grc:1081: double

...
uble
hbo:8600: double
hbo:8601: double
hbo:8602: double
hbo:8602a: double
hbo:8603: double
hbo:8604: double
hbo:8605: double
hbo:8606: double
hbo:8607: double
hbo:8608: double
hbo:8609: double
hbo:8610: double
hbo:8611: double
hbo:8612: double
hbo:8613: double
hbo:8614: double
hbo:8615: double
hbo:8615a: double
hbo:8616: double
hbo:8616a: double
hbo:8617: double
hbo:8618: double
hbo:8619: double
hbo:8620: double
hbo:8621: double
hbo:8622: double
hbo:8623: double
hbo:8624: double
hbo:8625a: double
hbo:8626: double
hbo:8627: double
hbo:8628: double
hbo:8629: double
hbo:8630: double
hbo:8631: double
hbo:8632: double
hbo:8632a: double
hbo:8633: double
hbo:8634: double
hbo:8635: double
hbo:8636: double
hbo:8638: double
hbo:8639: double
hbo:8640: double
hbo:8641: double
hbo:8642: double
hbo:8643: double
hbo:8644: double
hbo:8645: double
hbo:8646: double
hbo:8646a: double
hbo:8647: double
hbo:8649: double
hbo:8649b: double
hbo:8650: double
hbo:8651: double
hbo:8652: double
hbo:8653: double
hbo:8654: double
hbo:8655: double
hbo:8656: double
hbo:8656a: double
hbo:8657: double
hbo:8658: double
hbo:8659: double
hbo:8659a: double
hbo:8660: double
hbo:8661: double
hbo:8662: double
hbo:8663: double
hbo:8664: double
hbo:8665: double
hbo:8666: double
hbo:8667: int64
hbo:8668: double
hbo:8669: double
hbo:8670: double
hbo:8674: double
lexemes: int64
content_sha256: string
min_langs: int64
-- schema metadata --
pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 1754835
to
{'content_sha256': Value('string'), 'lexemes': Value('int64'), 'min_langs': Value('int64')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                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: JSON parse error: The document is empty.
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 483, 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 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 339, in _generate_tables
                  yield Key(shard_idx, 0), self._cast_table(pa_table)
                                           ~~~~~~~~~~~~~~~~^^^^^^^^^^
                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
              grc:1: double
              grc:10: double
              grc:100: double
              grc:1000: double
              grc:1001: double
              grc:1003: double
              grc:1004: double
              grc:1005: double
              grc:1006: double
              grc:1007: double
              grc:1008: double
              grc:1009: double
              grc:101: double
              grc:1010: double
              grc:1011: double
              grc:1012: double
              grc:1013: double
              grc:1014: double
              grc:1015: double
              grc:1016: double
              grc:1017: double
              grc:1018: double
              grc:1019: double
              grc:102: double
              grc:1020: double
              grc:1021: double
              grc:1022: double
              grc:1023: double
              grc:1024: double
              grc:1025: double
              grc:1026: double
              grc:1027: double
              grc:1028: double
              grc:1029: double
              grc:103: double
              grc:1030: double
              grc:1031: double
              grc:1032: double
              grc:1033: double
              grc:1034: double
              grc:1035: double
              grc:1036: double
              grc:1037: double
              grc:1038: double
              grc:1039: double
              grc:1040: double
              grc:1041: double
              grc:1042: double
              grc:1043: double
              grc:1044: double
              grc:1045: double
              grc:1046: double
              grc:1047: double
              grc:1048: double
              grc:1049: double
              grc:105: double
              grc:1050: double
              grc:1051: double
              grc:1052: double
              grc:1053: double
              grc:1054: double
              grc:1055: double
              grc:1056: double
              grc:1057: double
              grc:1058: double
              grc:1059: double
              grc:106: double
              grc:1060: double
              grc:1061: double
              grc:1062: double
              grc:1064: double
              grc:1066: double
              grc:1067: double
              grc:1068: double
              grc:1069: double
              grc:107: double
              grc:1070: double
              grc:1071: double
              grc:1072: double
              grc:1073: double
              grc:1074: double
              grc:1075: double
              grc:1076: double
              grc:1077: double
              grc:1078: double
              grc:1079: double
              grc:108: double
              grc:1080: double
              grc:1081: double
              
              ...
              uble
              hbo:8600: double
              hbo:8601: double
              hbo:8602: double
              hbo:8602a: double
              hbo:8603: double
              hbo:8604: double
              hbo:8605: double
              hbo:8606: double
              hbo:8607: double
              hbo:8608: double
              hbo:8609: double
              hbo:8610: double
              hbo:8611: double
              hbo:8612: double
              hbo:8613: double
              hbo:8614: double
              hbo:8615: double
              hbo:8615a: double
              hbo:8616: double
              hbo:8616a: double
              hbo:8617: double
              hbo:8618: double
              hbo:8619: double
              hbo:8620: double
              hbo:8621: double
              hbo:8622: double
              hbo:8623: double
              hbo:8624: double
              hbo:8625a: double
              hbo:8626: double
              hbo:8627: double
              hbo:8628: double
              hbo:8629: double
              hbo:8630: double
              hbo:8631: double
              hbo:8632: double
              hbo:8632a: double
              hbo:8633: double
              hbo:8634: double
              hbo:8635: double
              hbo:8636: double
              hbo:8638: double
              hbo:8639: double
              hbo:8640: double
              hbo:8641: double
              hbo:8642: double
              hbo:8643: double
              hbo:8644: double
              hbo:8645: double
              hbo:8646: double
              hbo:8646a: double
              hbo:8647: double
              hbo:8649: double
              hbo:8649b: double
              hbo:8650: double
              hbo:8651: double
              hbo:8652: double
              hbo:8653: double
              hbo:8654: double
              hbo:8655: double
              hbo:8656: double
              hbo:8656a: double
              hbo:8657: double
              hbo:8658: double
              hbo:8659: double
              hbo:8659a: double
              hbo:8660: double
              hbo:8661: double
              hbo:8662: double
              hbo:8663: double
              hbo:8664: double
              hbo:8665: double
              hbo:8666: double
              hbo:8667: int64
              hbo:8668: double
              hbo:8669: double
              hbo:8670: double
              hbo:8674: double
              lexemes: int64
              content_sha256: string
              min_langs: int64
              -- schema metadata --
              pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 1754835
              to
              {'content_sha256': Value('string'), 'lexemes': Value('int64'), 'min_langs': Value('int64')}
              because column names don't match

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cross-lingual-span-profile

A per-MACULA-lexeme structural profile — span length / multi-word tendency — aggregated across every language the lexeme-aligner has aligned. Every language anchors to the same lexeme, so this is a language-independent INTERLINGUA signal: it tells you whether a Hebrew/Greek lexeme typically needs a single target word or a multi-word phrase (compound place names — "Kadesh Barnea" — compound numbers — "four thousand"), based on what OTHER languages actually did, with NO target-language model for the language you're applying it to.

n_langs = how many independent languages (editions of the same language pooled first, so a 2-edition language doesn't out-vote a 1-edition one) attest the lexeme; multiword_rate/span_mean = the per- language-averaged span statistics. Confidence scales with n_langs — refresh as more languages are aligned (see the lexeme-aligner's cross_lang_prior.py).

CC0-1.0 — derived alignment statistics, no source text redistributed.

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