DigitalAsocial/all-mpnet-base-v2-ds-rag-5g
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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ArrowInvalid
Message: JSON parse error: Column() changed from object to string in row 0
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 174, in _generate_tables
df = pandas_read_json(f)
^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1391, in _parse
self.obj = DataFrame(
^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/core/frame.py", line 778, in __init__
mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/core/internals/construction.py", line 503, in dict_to_mgr
return arrays_to_mgr(arrays, columns, index, dtype=dtype, typ=typ, consolidate=copy)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/core/internals/construction.py", line 114, in arrays_to_mgr
index = _extract_index(arrays)
^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/core/internals/construction.py", line 677, in _extract_index
raise ValueError("All arrays must be of the same length")
ValueError: All arrays must be of the same length
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
return next(iter(self.iter(batch_size=n)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
for key, example in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 503, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 350, 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 177, in _generate_tables
raise e
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 151, in _generate_tables
pa_table = paj.read_json(
^^^^^^^^^^^^^^
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
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Card: Processed 5 Scientific Books Sentence Pairs Dataset Description Language: English (scientific/technical domain)
License: Research use only (derived from copyrighted books, full texts not redistributed)
Dataset Summary: This dataset contains sentence pairs extracted from 5 scientific books. Each book was processed with GROBID to obtain structured text from PDF files. Sentences were segmented and paired for training sentence-transformer models on semantic similarity tasks. To ensure balance, a maximum of 6,000 sentences per book was included. Dataset Structure Data Instances Each entry is a pair of sentences:
{
"sentence_0": "Some of the generated samples that had been achieved with this architecture already in 2014 can be seen in Figure 3.14.",
"sentence_1": "Conditioning on Text: So far, only image generation has been covered, completely ignoring textual input."
}
Data Splits All data is in the "train" split.
Total size: ~66424 sentence pairs.
Balanced across 5 books (≤6000 sentences per book).
Dataset Creation Curation Rationale The dataset was created to provide high-quality sentence pairs for training and evaluating sentence-transformer models in the scientific domain. Limiting to 6000 sentences per book ensures balanced representation and reduces copyright risks.
Source Data Books: 5 scientific/technical books (copyrighted, not redistributed).
Extraction: PDFs processed with GROBID → structured text → sentence segmentation (NLTK).
Pairs: Constructed from consecutive sentences and curated positive/negative examples.
Data Extraction Logic Raw PDFs processed with GROBID.
Sentences segmented with NLTK.
Maximum 6000 sentences per book included.
Sentence pairs generated for semantic similarity training.
Additional Information Citation If you use this dataset, please cite:
@misc{aghakhani2025synergsticrag,
author = {Danial Aghakhani Zadeh},
title = {Processed 5 Scientific Books Sentence Pairs},
year = {2025},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/datasets/DigitalAsocial/ds-tb-5-g}}
}
Personal and Sensitive Information The dataset consists of scientific/technical text.
No personal or sensitive information is included.
Bias, Risks, and Limitations Texts reflect the style and biases of their original authors.
Dataset is domain-specific (scientific books) and may not generalize to everyday language.
Full copyrighted texts are not included; only derived sentence pairs are shared.
Notice and Takedown Policy If you believe this dataset contains material that infringes copyright, please contact us with:
Your contact information
Reference to the original work
Identification of the material claimed to be infringing
We will comply with legitimate requests by removing affected sources from future releases.
Dataset Curators Created by Danial for research on sentence-transformers and semantic similarity.
License Derived from copyrighted books.
Shared under Research Use Only license.
Full texts are not redistributed.
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