The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/httpx/_transports/default.py", line 101, in map_httpcore_exceptions
yield
File "/usr/local/lib/python3.14/site-packages/httpx/_transports/default.py", line 250, in handle_request
resp = self._pool.handle_request(req)
File "/usr/local/lib/python3.14/site-packages/httpcore/_sync/connection_pool.py", line 256, in handle_request
raise exc from None
File "/usr/local/lib/python3.14/site-packages/httpcore/_sync/connection_pool.py", line 236, in handle_request
response = connection.handle_request(
pool_request.request
)
File "/usr/local/lib/python3.14/site-packages/httpcore/_sync/connection.py", line 101, in handle_request
raise exc
File "/usr/local/lib/python3.14/site-packages/httpcore/_sync/connection.py", line 78, in handle_request
stream = self._connect(request)
File "/usr/local/lib/python3.14/site-packages/httpcore/_sync/connection.py", line 124, in _connect
stream = self._network_backend.connect_tcp(**kwargs)
File "/usr/local/lib/python3.14/site-packages/httpcore/_backends/sync.py", line 207, in connect_tcp
with map_exceptions(exc_map):
~~~~~~~~~~~~~~^^^^^^^^^
File "/usr/local/lib/python3.14/contextlib.py", line 162, in __exit__
self.gen.throw(value)
~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/httpcore/_exceptions.py", line 14, in map_exceptions
raise to_exc(exc) from exc
httpcore.ConnectTimeout: timed out
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 844, in read_with_retries
out = read(*args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_file_system.py", line 1238, in read
return super().read(length)
~~~~~~~~~~~~^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/fsspec/spec.py", line 1897, in read
out = self.cache._fetch(self.loc, self.loc + length)
File "/usr/local/lib/python3.14/site-packages/fsspec/caching.py", line 234, in _fetch
self.cache = self.fetcher(start, end) # new block replaces old
~~~~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_file_system.py", line 1194, in _fetch_range
r = http_backoff("GET", url, headers=headers, timeout=constants.HF_HUB_DOWNLOAD_TIMEOUT)
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_http.py", line 559, in http_backoff
return next(
_http_backoff_base(
...<9 lines>...
)
)
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_http.py", line 479, in _http_backoff_base
raise err
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_http.py", line 467, in _http_backoff_base
response = client.request(method=method, url=url, **kwargs)
File "/usr/local/lib/python3.14/site-packages/httpx/_client.py", line 825, in request
return self.send(request, auth=auth, follow_redirects=follow_redirects)
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/httpx/_client.py", line 914, in send
response = self._send_handling_auth(
request,
...<2 lines>...
history=[],
)
File "/usr/local/lib/python3.14/site-packages/httpx/_client.py", line 942, in _send_handling_auth
response = self._send_handling_redirects(
request,
follow_redirects=follow_redirects,
history=history,
)
File "/usr/local/lib/python3.14/site-packages/httpx/_client.py", line 979, in _send_handling_redirects
response = self._send_single_request(request)
File "/usr/local/lib/python3.14/site-packages/httpx/_client.py", line 1014, in _send_single_request
response = transport.handle_request(request)
File "/usr/local/lib/python3.14/site-packages/httpx/_transports/default.py", line 249, in handle_request
with map_httpcore_exceptions():
~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/contextlib.py", line 162, in __exit__
self.gen.throw(value)
~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/httpx/_transports/default.py", line 118, in map_httpcore_exceptions
raise mapped_exc(message) from exc
httpx.ConnectTimeout: timed out
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/parquet/parquet.py", line 127, in _split_generators
self.info.features = datasets.Features.from_arrow_schema(pq.read_schema(f))
~~~~~~~~~~~~~~^^^
File "/usr/local/lib/python3.14/site-packages/pyarrow/parquet/core.py", line 2424, in read_schema
file = ParquetFile(
where, memory_map=memory_map,
decryption_properties=decryption_properties)
File "/usr/local/lib/python3.14/site-packages/pyarrow/parquet/core.py", line 328, in __init__
self.reader.open(
~~~~~~~~~~~~~~~~^
source, use_memory_map=memory_map,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
...<8 lines>...
arrow_extensions_enabled=arrow_extensions_enabled,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "pyarrow/_parquet.pyx", line 1656, in pyarrow._parquet.ParquetReader.open
File "pyarrow/error.pxi", line 89, in pyarrow.lib.check_status
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 869, in read_with_retries
raise ConnectionError("Server Disconnected") from disconnect_err
ConnectionError: Server Disconnected
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/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
YAML Metadata Warning:The task_categories "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
NbAiLab/nb-asr-supermorphed-nob
This dataset teaches direct conversion from ordinary Norwegian Bokmål text to AltMorph bracket encoding. Every clean row contains an original source and one validated target. Allowed alternatives inside a block are alphabetized and use the form [alternativ1|alternativ2].
Splits
| Split | Rows | Source words |
|---|---|---|
| train | 349,692 | 9,012,203 |
| validation | 1,000 | 25,419 |
| test | 1,000 | 27,964 |
Validation and test contain exactly 1,000 rows each. They were selected only after cleaning with a fixed random document-level hash. No other row from a held-out upstream document appears in train. Test contents were not manually inspected after assignment.
Provenance and licenses
Each row retains source_dataset, immutable source_revision, source_row_id, source_document_id, source_type, and license. The corpus contains material under several compatible open licenses, so the Hub-level license is marked other; the authoritative license for reuse is the row-level license value. Consult the upstream dataset cards as well.
Construction
The build used only upstream train material. Text was NFC- and whitespace-normalized and split into rows of at most 200 whitespace words during collection. Collected rows remain available for later rounds, while this release selects at most 10 million source words and excludes rows over 120 words. Only exact normalized duplicates were removed, with lineage retained in the private build audit. Målfrid was excluded by provenance after source-quality analysis and contributes no release rows.
Every deduplicated row was scored by the pinned NbAiLab/nb-nordic-lid models
nb-nordic-lid.159.ftz and nb-nordic-lid.ftz at revision
12401f3e0d4e73adf86a089e828d82d37242ccab (OpenRAIL). LID was used only as a
high-confidence foreign-text veto; it never assigned Bokmål versus Nynorsk.
Either Norwegian label passed. Broad non-Norwegian predictions required at
least 12 words and confidence 0.99. Danish, Swedish, Faroese, and Icelandic
required at least 40 words and matching 0.99 predictions from both models.
Raw LID labels and scores are retained in the private build audit and are not
published as dataset columns.
A pinned multilingual E5 encoder assigned deterministic cosine-LSH clusters. Sampling used source type, length, and semantic cluster jointly, with a document cap outside parliamentary transcripts and a square-root length cost that mildly favors shorter rows without imposing a percentile quota.
Two candidate generators were compared in a teacher/student workflow. The
rule-based teacher candidate used
AltMorph revision 895347c82c07f6e4f7e2d3afec838291838c4c87, HumIT
Humit-Oslo/humit-tagger-large at revision 942f2901ec3271c9f627eb6a78b07ade87cf8126, Ordbank with mandatory
complete inflection search, and North-T5 north/t5_base_NCC at revision
23788220cee2fb254bb0aa175074a5dd03f8d763.
The launch-time Git worktree dirty flag was
true; the authoritative
implementation fingerprint was 1b32b0f68f2bb94e513feefba439ae075c701875e12e9989214aeab1256b0328 and
the run-contract SHA-256 was dbcf6b3fff9ce873f4e8c48d6014f1fbd00aefa7f370a3a59444bd148bc22f86. Generation
used 4 shards, batches of
100 rows, HumIT/North-T5 batches of
16/16, and
4 local cache-lookup threads per worker. Corpus generation was cache-only and could not contact Ordbank.
The model candidate used google/t5gemma-2-1b-1b at revision
dd0a2683227859151b1730ca3a63087df5b5f39b. A separate model for
nob was fine-tuned for exactly
1 epoch on the complete strict AltMorph teacher corpus
local-supermorph-teacher-nob, pinned by manifest SHA-256
e7d708fc8ae4b633d81c0ea342852909764422f77b374f199b4de5589c7fdb8b. Its deterministic teacher_eval
view overlaps training and is only a consistency diagnostic, not held-out
validation. Run t5gemma2-1b-supermorph-nob-1ep-l40s-micro4-math-v1 used the final checkpoint at step
2900 (final checkpoint after exactly one language-specific epoch) and reached exact match
0.923000. Greedy inference used batch size
8, with source/target limits of
768/768 tokens. The resolved
training configuration SHA-256 was 00d8e1d211caf05859714f076ee1a25b4de843955ff0ef5b3fccbb7950cadf78.
Valid exact agreements were accepted automatically. Their rate was 94.72%; blind-review packet creation required at least 90.00%. The 19,605 disagreements were shown independently to three blind reviewers. Candidate provenance was hidden and A/B order was randomized separately for every reviewer. Reviewers could select only A, B, or None and could not edit text. A disagreement was retained only when all three selected the same underlying structurally valid candidate.
The audit configuration preserves rejected rows, both candidates, decoded votes, and rejection status. It also preserves accepted companions excluded solely to prevent held-out-document leakage. These rows can be reconsidered by future models; they were not silently deleted.
Cleaning summary
- automatic valid agreements: 351,556
- accepted by three-reviewer consensus: 369
- rejected or unresolved before split isolation: 19,236
- held-out document companions moved to audit: 233
Build scripts and the complete reproducibility contract are maintained in the AltMorph repository under dataset_tools/supermorphed/.
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