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Error code: DatasetGenerationError Exception: CastError Message: Couldn't cast directory: string identifier: string ...1: int64 creator: string language: string title: string publication_date: int64 lang: string real_lang: string n: int64 rights: string file: string word_count: int64 text: string -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1844 to {'identifier': Value(dtype='string', id=None), 'creator': Value(dtype='string', id=None), 'title': Value(dtype='string', id=None), 'publication_date': Value(dtype='string', id=None), 'word_count': Value(dtype='string', id=None), 'text': Value(dtype='string', id=None), '__index_level_0__': Value(dtype='int64', id=None)} because column names don't match Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1492, in compute_config_parquet_and_info_response fill_builder_info(builder, hf_endpoint=hf_endpoint, hf_token=hf_token, validate=validate) File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 683, in fill_builder_info ) = retry_validate_get_features_num_examples_size_and_compression_ratio( File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 602, in retry_validate_get_features_num_examples_size_and_compression_ratio validate(pf) File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 640, in validate raise TooBigRowGroupsError( worker.job_runners.config.parquet_and_info.TooBigRowGroupsError: Parquet file has too big row groups. First row group has 433980469 which exceeds the limit of 300000000 During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1995, in _prepare_split_single for _, table in generator: File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 797, in wrapped for item in generator(*args, **kwargs): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 97, in _generate_tables yield f"{file_idx}_{batch_idx}", self._cast_table(pa_table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 75, in _cast_table pa_table = table_cast(pa_table, self.info.features.arrow_schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast return cast_table_to_schema(table, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema raise CastError( datasets.table.CastError: Couldn't cast directory: string identifier: string ...1: int64 creator: string language: string title: string publication_date: int64 lang: string real_lang: string n: int64 rights: string file: string word_count: int64 text: string -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1844 to {'identifier': Value(dtype='string', id=None), 'creator': Value(dtype='string', id=None), 'title': Value(dtype='string', id=None), 'publication_date': Value(dtype='string', id=None), 'word_count': Value(dtype='string', id=None), 'text': Value(dtype='string', id=None), '__index_level_0__': Value(dtype='int64', id=None)} 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 1505, in compute_config_parquet_and_info_response parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet( File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1099, in stream_convert_to_parquet builder._prepare_split( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2038, in _prepare_split_single raise DatasetGenerationError("An error occurred while generating the dataset") from e datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset
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identifier
string | creator
string | title
string | publication_date
string | word_count
string | text
string | __index_level_0__
int64 |
---|---|---|---|---|---|---|
0000048348 | Gil y Robles, Enrique , 1849-1908 // | Apuntes de Derecho Político según el indice-programa de la obra del Sr. Gil y Robles | 1903 - 1904 | 215781 | "_\n\nja\n\nfe\n\n.\n\nV\n\n*\n\n^\n\n-\n\n.\n\n.... ,.\n\n' <^\n\nv\n\n' <gí\n\ne s ? . * \"\n\n\n(...TRUNCATED) | 1 |
0000085124 | Marcoartu, Arturo de , 1827-1904 // | Líneas submarinas telegráficas de Europa a las Américas, del Atlántico al Pacífico | 1863 | 12134 | "\n\n\n\n\n\nEMPRESA\n\nTELEGRAFICA\n\nUNIVERSAL.\n\nLINEAS\n\n8UBMAEINA8\n\nTELEGEAFIOAS\n\nDE EURO(...TRUNCATED) | 2 |
0000206732 | nan | Pasión infame (un espantoso drama de adulterio) | 1900? | 7393 | "COLECCION\n\nESCOGIDA\n\nA\n\nO\n\nC T S.\n\nPOPULAR .Versos para postales, cartas, álbuizis y aba(...TRUNCATED) | 3 |
0000234020 | Maura y Montaner, Antonio , 1853-1925 // Catalá y Gavilá, Juan Bautista , n. 1861 // | Ideario político | 1918 | 72390 | "T\n« i? ORADOilES\nColección de sus o b ra s m aestras\nV Esta Bibüute«?» cout«adrá, en libr(...TRUNCATED) | 4 |
0000259618 | "Medina Sarauz, Catalina de -ptf // Rueda, Miguel de -demandante ptf // Muriel, Catalina -demandan(...TRUNCATED) | "Por doña Catalina de Medina Sarauz, biuda del Secretario Alonso Muriel, y vsufructuaria de sus bie(...TRUNCATED) | 1607 | 3010 | "Doña Catalina de\nna\n\nMedi-\n\nSarauz, biuda del\n\nSecretario Alonfb\n\nfus bienes: Miguel de R(...TRUNCATED) | 7 |
0000191362 | Nicolas, Auguste , 1807-1888 // | Estudios filosóficos sobre el cristianismo | 1845 - 1846 | 594086 | "\n1\n\n\n\n\nESTUDIOS FILOSOFICOS\n\nson lili\n\nEL CRISTIANISMO.\n\n\n\nESTUDIOS FILOSOFICOS\nSO V(...TRUNCATED) | 8 |
0000107438 | Le Bas, Philippe , 1794-1860 // | Manual de historia romana, desde la fundación de Roma hasta la caída del Imperio de Occidente | 1845 | 222071 | "© Biblioteca Nacional de España\n\n\n© Biblioteca Nacional de España\n\n\nJ\n© Biblioteca Naci(...TRUNCATED) | 10 |
0000073100 | Gómez de Avellaneda, Gertrudis , 1814-1873 // | La hija de las flores o Todos están locos drama en tres actos y en verso | 1852 | 21751 | "\n\n\n\nLA HUÍ DE U S FLORES,\nó\nDRAMA EN T R E S ACTOS, Y EN VERSO, POR\n\nLA EXMA. SRA. DOÑA (...TRUNCATED) | 12 |
0000142917 | San Miguel y de Otero, Vizconde de // | "Soneto acrostico a la muerte de la Reyna nuestra señora doña Maria Luisa de Borbon, que goza de D(...TRUNCATED) | 1689 | 349 | "•\n\n© Biblioteca Nacional de España\n\n\n© Biblioteca Nacional de España\n\n\n,\n\n•\n\n(...TRUNCATED) | 15 |
0000107159 | Sardá y Salvany, Félix , 1844-1916 // | Los frailes holgazanes | 1899 | 2921 | "DETODO EL M U N D O\nР О В\n\nS. ? S. ;\nLUI.\n\nÎLos iraiïe»\n\nborane*.\n\n\nCON L I C E N (...TRUNCATED) | 16 |
🇪🇸 Spanish Public Domain Books 🇪🇸
Spanish-Public Domain-Newspapers or Spanish-PD-Newspapers is a large collection aiming to aggregate all Spanish monographies in the public domain. As of March 2024, with Spanish-PD-Newspapers, it is the biggest Spanish open corpus.
Dataset summary
The collection contains 302,640 individual texts making up 13.9 billion words recovered from multiple sources, including Spanish leading cultural heritage institution Biblioteca Digitale Hispanica (BDH) and Internet Archive. Each parquet file has the full text of 2,000 books selected at random.
Curation method
The composition of the dataset adheres to the criteria for public domain works in the EU and, consequently, all Berne-countries for EU authors: any publication whose author is dead for more than 70 years. Additionally, the initial consolidation of public domain status for cultural heritage operates in the EU under the 2019 Copyright Directive (art. 14).
Uses
The collection aims to expand the availability of open works for the training of Large Language Models. The text can be used for model training and republished without restriction for reproducibility purposes.
The rationales for creation of this collection are multifold:
- Scientific: We observe that the closure of training corpora represents a major barrier to AI research. Large language models face a real crisis of reproducibility.
- Legal: With the adoption of the AI Act with its obligations in terms of copyright law compliance for the pretraining corpora, the European AI ecosystem will have to change its provenance practices.
- Cultural: The linguistic diversity of the European Union is currently underrepresented. Unlike web archives, open, heritage, administrative, or scientific texts are often of high quality: they are long, multilingual, and editorialized publications.
- Economical: Today, value capture is concentrated on players whose financial resources are already considerable, allowing them to collect or purchase data at a high price. Making a royalty-free corpus available to as many people as possible frees innovation in uses and minimizes economic dependencies on dominant actors.
License
The entire collection is in the public domain in all regions. This means that the patrimonial rights of each individual or collective right holders have expired.
There has been a debate for years in Europe over the definition of public domain and the possibility to restrict its use. Since 2019, the EU Copyright Directive states that "Member States shall provide that, when the term of protection of a work of visual art has expired, any material resulting from an act of reproduction of that work is not subject to copyright or related rights, unless the material resulting from that act of reproduction is original in the sense that it is the author's own intellectual creation." (art. 14)
Future work
This dataset is not a one-time work but will continue to evolve significantly in three directions:
- Expansion of the dataset to the late 19th and early 20th century works and its further enhancement with currently unexploited collections coming from European patrimonial data repositories.
- Correction of computer generated errors in the text. All the texts have been transcribed automatically through the use of Optical Character Recognition (OCR) software. The original files have been digitized over a long time period (since the mid-2000s) and some documents should be. Future versions will strive either to re-OCRize the original text or use experimental LLM models for partial OCR correction.
- Enhancement of the structure/editorial presentation of the original text. Some parts of the original documents are likely unwanted for large scale analysis or model training (header, page count…). Additionally, some advanced document structures like tables or multi-column layout are unlikely to be well-formatted.
Acknowledgements
The corpus was stored and processed with the generous support of Scaleway. It was built up with the support and concerted efforts of the state start-up LANGU:IA (start-up d’Etat), supported by the French Ministry of Culture and DINUM, as part of the prefiguration of the service offering of the Alliance for Language technologies EDIC (ALT-EDIC).
Corpus collection has been largely facilitated thanks to the open science LLM community insights, cooperation and support (Occiglot, Eleuther AI, OpenLLM France, Allen AI).
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