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Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
fn: list<item: string>
child 0, item: string
wp: list<item: string>
child 0, item: string
fp: list<item: string>
child 0, item: string
rows: list<item: string>
child 0, item: string
to
{'text': 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 1848, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 783, in write_table
self.write_rows_on_file() # in case there are buffered rows to write first
~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
self._write_table(table)
~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 795, in _write_table
pa_table = table_cast(pa_table, self._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
fn: list<item: string>
child 0, item: string
wp: list<item: string>
child 0, item: string
fp: list<item: string>
child 0, item: string
rows: list<item: string>
child 0, item: string
to
{'text': Value('string')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 4 new columns ({'fn', 'fp', 'rows', 'wp'}) and 1 missing columns ({'text'}).
This happened while the json dataset builder was generating data using
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'hf://datasets/bcv-commons/full-alignments-llm@49f2972c6201f39ccc90f2a9bcf236a8272362d0/e/ell/ell_GreVamvas+llm+jev-v4/ZEP_1f88b53b.meta.json', 'hf://datasets/bcv-commons/full-alignments-llm@49f2972c6201f39ccc90f2a9bcf236a8272362d0/e/ell/ell_GreVamvas+llm+jev-v4/_layer.json', 'hf://datasets/bcv-commons/full-alignments-llm@49f2972c6201f39ccc90f2a9bcf236a8272362d0/manifest.json']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1868, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 803, in finalize
self.write_rows_on_file()
~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
self._write_table(table)
~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 795, in _write_table
pa_table = table_cast(pa_table, self._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
fn: list<item: string>
child 0, item: string
wp: list<item: string>
child 0, item: string
fp: list<item: string>
child 0, item: string
rows: list<item: string>
child 0, item: string
to
{'text': 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 datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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0:0 1:1-2 2:3 3:5 4:7 5:9 6:11,14 7:15 8:17 9:18-19 10:21 |
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0:3 1:4 2:6 3:7-8 4:11 5:15 6:17 7:19 8:22-23 9:24 10:26 |
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0:2 1:5 2:8 3:9 4:10 5:12-13 6:14-15 |
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0:1 1:3 2:5 3:6 4:8-9 5:10-11 6:13-14 |
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0:0-1 1:2 2:3 3:5 4:6 5:8 6:9 7:11 8:13 |
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0:1 1:2,10 2:4 3:6 4:7 5:3,9 6:11 |
0:0 1:1-2 2:3 3:5 4:7 5:8 6:10 7:12 8:13-14 9:15 10:17 |
0:0 1:1-2 2:3 3:5 4:6-7 5:8 6:10 7:12 8:14 |
0:0 1:1-2 2:3 3:5 4:7 5:8 6:9-10 7:11 8:13 |
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0:1 1:2-3 2:4 3:6 4:7-8 5:11 6:12-14 |
0:1 1:2-3 2:4 |
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0:1 1:4 2:6 3:8 4:9-10 5:11 6:13 7:15 |
0:2 1:3 2:5 3:7-9 5:10-11 6:13 !4 |
0:1 1:2-3 2:4-5 3:6-7 4:10 5:11-12 6:17 7:19 8:20 9:23 10:25 11:27 |
0:0 1:2-3 2:6 3:5 4:10 5:12 6:16 |
0:1 1:2 2:4 3:7 4:8 5:10 |
0:3 1:4-5 2:7-8 3:9-10 4:11-13 6:16 7:18 8:21 9:23 10:27 !5 |
0:1 1:2 2:4 3:6 4:8 5:10-11 6:12 |
0:1 1:4 2:6 3:8 4:9 5:11 6:14 7:17 8:18 9:19 10:21-22 11:23-24 12:25-26 13:27 |
1:4 2:5-6 3:9-11 5:7 6:12 7:15 8:16-17 9:18-19 !0,4 |
0:1,8 1:2 2:3-4 3:5-7 5:11 6:9 7:13 8:15 9:17 10:19 !4 |
1:5 2:4 3:1 4:8-9 5:11 6:14-15 7:16 !0 |
0:1,8 1:2 2:3-4 3:5-6 4:7 5:9 6:11 7:13 |
0:1,5 2:3-4 3:6 4:8 5:2,10 6:12-13 7:14 8:16 !1 |
0:1-2 1:3-4 2:5-6 3:8 4:10 5:14 6:17 |
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0:1,14 1:3-4 2:5 3:7 4:9-10 5:11 6:2,13 7:15-16 8:17 |
0:1-2 1:3-4 2:5-6 3:7 4:8 5:10 6:11 7:13-14 8:15 |
0:1 1:3-4 2:5 3:7 4:8 5:9 6:2,10 7:12-13 |
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0:0,2 1:3-4 2:5-6 3:7 4:9 5:11 6:15-16 7:17-18 8:20-21 9:22-23 10:24-25 11:26 |
0:1-2 1:3-4 2:5 3:7 4:9 5:11 |
0:1-2 1:3 2:5 3:6-8 5:10-11 6:12 7:14 !4 |
0:1-2 1:3-4 2:5-6 3:7,9 4:10-11 5:12-13 |
0:2 1:3 2:4-5 3:6 4:8 5:11 6:14 7:16 8:17 9:19 |
full-alignments-llm — full word alignments checked by a language model
Every word of a verse, linked to the Hebrew or Greek source word it translates, function words included (articles, prepositions, particles, clitic pronouns), and the source words that have no target word of their own marked explicitly. Each layer starts from the statistical alignment of compact-alignments and has every verse checked by a language model, which keeps, changes or adds links. These are machine alignments: no person has checked them. Hand-made alignments are in full-alignments-manual.
The files use the format of compact-alignments (same paths, same _index/, same tokenizer), so a compact reader works on them
unchanged. The extra channels and the decision-list encoding are those of full-alignments-manual, section "File format".
Layers
A layer id is <edition>+llm+<name>, where <edition> is the compact-alignments edition id of the same text, e.g.
e/ell/ell_GreVamvas+llm+jev-v4/. The list of layers, with rows and books, is in manifest.json.
| layer | text | model and method | rows |
|---|---|---|---|
ell_GreVamvas+llm+jev-v4 |
Neophytos Vamvas 1850, Modern Greek (public domain; CrossWire GreVamvas via bcv-commons/bibles), 66 books | TypeSafe Jev (jev-1.13.0), design v4 |
605,084 |
Design v4: for each verse the model is asked about every target function word and every source function word, and about each
content link the chain flagged as doubtful: which source word a target word belongs to, or which target word carries a source word.
Each row records in its profile (_layer.json) whether the link was kept from the chain (llm_edit_kept, with the chain method
that proposed it), edited by the model (llm_edit_edited) or is a function word carried inside another word, for example by a
prefix or suffix (llm_edit_inside). A source word the model leaves unrendered is an explicit no-rendering (!). Verses with nothing to
ask (mostly name lists) or no target text keep the chain's proposal. Model version, design and threshold are in each layer's
_layer.json. The questions are built by lexeme_aligner.eval.jev_check and the layer by lexeme_aligner.fullalign_build
(github.com/bcv-commons/lexeme-aligner).
File format
<iso[0]>/<iso>/<layer id>/<BOOK>_<hash>.json main: "srcOrd:span ..." per spine verse, as in compact-alignments
<iso[0]>/<iso>/<layer id>/<BOOK>_<hash>.meta.json channels (function words, profiles, rows), see full-alignments-manual
<iso[0]>/<iso>/<layer id>/_layer.json version, flags, spine index sha, attribution, profile table
<hash> = the first 8 hex characters of the book's text fingerprint (compact-alignments README, "The text fingerprint"), the same
name the compact file of that text has, so a file only matches the exact text it was built on. No file holds a word of any text.
Verse mapping
Spans are keyed by the source verse (Hebrew WLC numbering in the OT); read the target words from the edition's mapped verse (compact-alignments README, "Verse numbering"). Source and target verses are paired with the verse-mapping tables of TVTMS (STEPBible Data, Tyndale House, Cambridge — CC BY 4.0, https://github.com/STEPBible/STEPBible-Data).
License
The alignments are CC0 1.0. They hold no text; the edition named by each layer keeps its own licence (Vamvas: public domain).
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