The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ParserError
Message: Error tokenizing data. C error: Expected 1 fields in line 8, saw 6
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 249, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
yield from 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/csv/csv.py", line 198, in _generate_tables
for batch_idx, df in enumerate(csv_file_reader):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
return self.get_chunk()
~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
return self.read(nrows=size)
~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1923, in read
) = self._engine.read( # type: ignore[attr-defined]
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
nrows
^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
chunks = self._reader.read_low_memory(nrows)
File "pandas/_libs/parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
File "pandas/_libs/parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "pandas/_libs/parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 8, saw 6Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Hebrew Word Senses
Which Biblical Hebrew lexemes are polysemous (have more than one distinct meaning), and how their occurrences cluster into each sense — 12,536 sense-rows across ~8,015 (lexeme, verbal-stem) groups.
Method
Sense-cluster structure (which occurrences belong to which sense) is decided entirely from Hebrew: occurrences of a (lexeme, stem) are grouped by their English gloss, then merged whenever their Hebrew- clause embedding centroids are close (single-linkage clustering) — the question "are these the same sense?" is answered by how the word is actually used in Hebrew context, not by an English label. No UBS/SDBH data is involved in this step at any point.
Gloss labels (the human-readable name for each sense) come from two sources:
- The dominant sense of each group (its most common meaning) uses
bcv-commons/strongs's own vetted gloss. - Every other (sub-)sense uses Cherith Glosses (Andi Wu, Copyright 2022, CC BY 4.0) via MACULA's
own
@glossattribute — confirmed via MACULA-Hebrew's own LICENSE to be a distinct, separately-licensed source, not SDBH/UBS MARBLE.
Columns
| column | meaning |
|---|---|
lex |
ETCBC/BHSA lexeme id |
stem |
verbal stem (binyan) — blank for non-verbs |
sense |
sense number within this (lex, stem) group; 1 is always the dominant sense |
gloss |
the English label for this sense (see Method above for provenance) |
count |
how many occurrences fall in this sense-cluster |
share |
count / the group's total occurrences — sense=1's share tells you how polysemous the word actually is in practice (a word with sense=1 at 99% share is barely polysemous despite having other senses tagged) |
License
CC BY 4.0. Sense-cluster structure: independently derived, no restricted source. Dominant-sense
glosses: from bcv-commons/strongs. Sub-sense glosses: Cherith Glosses (Andi Wu, CC BY 4.0), via
MACULA (Clear-Bible/macula-hebrew, CC BY 4.0) — not derived from or reproducing UBS MARBLE / SDBH.
Provenance
Built by bcv-RAG/scripts/cluster_senses_hebrew.py (clustering) and
shoresh/macula/build_hbo_lex_export.py (publish-ready gloss substitution) in
bcv-commons/bcv-query.
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