Datasets:
File size: 36,289 Bytes
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"target_bucket": "bulk_pretraining_web",
"priority": "high",
"notes": "European HPLT v1 has Polish web data (~1.89M docs / ~1.98B estimated tokens) with WDS quality score, language confidence, URL, MIME type, and web-register metadata. HF card/license says CC0-1.0 inherited from HPLT v3; keep web-crawl caveat, URL provenance, domain filtering, machine-translation filtering, and downstream dedup.",
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"it",
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"license: cc0-1.0",
"## Limitations",
"- **Tier-6 languages are data-limited** — Occitan, Scottish Gaelic, Faroese, Asturian have <250K docs each",
"## License",
"[CC0 1.0 Universal](https://creativecommons.org/publicdomain/zero/1.0/) — inherited from HPLT v3."
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"configured_decision": "accept_after_subset_review",
"target_bucket": "bulk_pretraining",
"priority": "high",
"notes": "Large open/traceable corpus with Polish coverage. Filter to Polish, non-legal, non-code, high-quality domains where metadata license is acceptable.",
"gated": false,
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"downloads": 83583,
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"la",
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"Common Corpus is the largest open licensed text dataset, comprising 2.27 trillion tokens (2,267,302,720,836 tokens). It is a diverse dataset, consisting of books, newspapers, scientific articles, government and legal documents, code, and more. Common Corpus has been created by Pleias in association with several partners.",
"* **Truly Open**: contains only data that is either uncopyrighted or freely licensed",
"* **Traceable**: each individual document is associated with documented contextual information, including licensed use or lack of copyright.",
"Common Corpus makes it possible to train model compatible with [the Open Source Initiative’s definition](https://opensource.org/ai/open-source-ai-definition#:~:text=An%20Open%20Source%20AI%20is,including%20to%20change%20its%20output.) of open-source AI, which includes openness of use, meaning use is permitted for “any purpose and without having to ask for permission\". Based on the available licensing information Common Corpus can be filtered to only include public domain works or a subset of free licenses (like attribution only).",
"* **OpenCulture**: our largest collection at 967,018,390,906 tokens, featuring public domain books, newspapers from cultural heritage repositories and open projets like Wikisource ad Gutenberg. We're developing innovative tools of OCR correction based on Pleias Models to correct historical digitization errors, while implementing advanced toxicity filtering to ensure content meets modern ethical standards.",
"| OpenCulture | cultural heritage | public domain books and newspapers, Wikisource |",
"The first version of [Common Corpus](https://huggingface.co/datasets/PleIAs/common_corpus) was released in November of 2024. The second version added Wikidata and detailed document-level information, including licensing and other core metadata whenever available. The third ongoing version dramatically expand the language coverage of Common Corpus beyond the US and Europe with the integration of large collection of documents in Chinese, Japanese, Arabic, Korean and Hindi.",
"* `license`: sharing rights for the content either uncopyrighted (public domain, US federal public domain, CC0 on Wikidata) or various free licenses (Creative Commons, MIT, French Licence ouverte, etc.)",
"* `date`: date of creation of the resource where known. Due to the significance of public domain and other cultural heritage content, more than half of Common Corpus predates the 21st century.",
"* `word_count`: number of space delimited words.",
"All data in Common Corpus are either uncopyrighted or freely licensed and may be used for both commercial and non-commercial purposes.",
"Some small parts of the French administrative common crawl have been entirely dropped using our unreleased small reasoning model for GDPR-filtering, due to the heightened risk of transmitting identifiable indirect personal information."
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"repo_id": "PleIAs/Polish-PD",
"configured_decision": "accept_after_ocr_review",
"target_bucket": "bulk_pretraining",
"priority": "high",
"notes": "Large public-domain Polish books/newspapers. Useful for scale, but OCR garbage must be measured aggressively.",
"gated": false,
"private": false,
"downloads": 518,
"license_tags": [],
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"# 🇵🇱 Polish Public Domain 🇵🇱",
"**Polish-Public Domain** or **Polish-PD** is a large collection aiming to aggregate all Polish monographies and periodicals in the public domain. As of March 2024, it is the biggest Polish open corpus.",
"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).",
"As of March 2024, to limit rights verification, we have retained exclusively titles published prior to 1884.",
"The corpus will be expanded at a later stage to encompass late 19th century and early 20th century publications, after checking for public domain validity.",
"* **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.",
"## 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)"
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"repo_id": "pelcra/PLLuMIC",
"configured_decision": "accept_gated",
"target_bucket": "final_phase_sft",
"priority": "high",
"notes": "High-quality hand-crafted Polish instruction/dialogue data. Use for SFT/final phase, not bulk pretraining.",
"gated": "auto",
"private": false,
"downloads": 33,
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"cc-by-sa-4.0"
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"pl"
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"license: cc-by-sa-4.0",
"- **License:** CC-BY-SA-4.0"
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"target_bucket": "qa_eval_final_phase",
"priority": "medium",
"notes": "CC-BY-SA Polish QA; passages are Wikipedia-heavy, so dedup against existing Wikipedia.",
"gated": false,
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"downloads": 214,
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"license: cc-by-sa-4.0",
"The passages proposed by the `hard-negative` and `zero-shot` methods are bound to be easier to retrieve by retrievers since they were proposed by such. To mitigate this bias, we include the passages found by the human annotators in an unconstrained way (`passage_source=\"human\"`). We hypothesize that it will result in more unbiased and diverse examples. Moreover, we asked the annotators to find not one but up to five passages, preferably from different articles to even further increase passage diversity.",
"### Other Known Limitations",
"The PolQA dataset focuses on trivia questions which might limit its usefulness in real-world applications since neural retrievers generalize poorly to other domains.",
"### Licensing Information"
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"notes": "CC-BY Polish QA. Keep as QA/eval/final-phase source.",
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"- cc-by-sa-4.0",
"FLORES+ is a multilingual machine translation benchmark released under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/). This dataset was originally released by FAIR researchers at Meta under the name FLORES. Further information about these initial releases can be found in [Dataset Sources](#dataset-sources) below. The data is now being managed by OLDI, [the Open Language Data Initiative](https://oldi.org/). The + has been added to the name to disambiguate between the original datasets and this new actively developed version.",
"- **License:** [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)",
"In order to show your agreement with the DCO you should include at the end of commit message,",
"This can be done easily using the `-s` flag on the `git commit`.",
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"extra_gated_prompt: \"**[IMPORTANT: We are forced to temporarily suspend access to OSCAR. The temporary nature of this suspension has led us to choose to implement it as gated access with manual control, and we will not grant any access until the situation has been clarified. We sincerely apologize for this situation and hope to be able to restore access as soon as possible. In the meantime, we remind you that we have always prohibited access to or use of OSCAR that violates the legislation in force where you are located. In France, for example, any use of OSCAR that does not fall within the framework of the so-called 'TDM' or the so-called 'research' exceptions to copyright has always been prohibited.]** By filling the form below, you understand that only the metadata and the annotations of OSCAR 23.01 have a cc0-1.0 license, and that the rest of the content is crawled data derived from the November/December 2022 snapshot of Common Crawl, for which the authors of OSCAR **do not** hold any copyright whatsoever.\"",
"- [Other Known Limitations](#other-known-limitations)",
"- [Licensing Information](#licensing-information)",
"### Other Known Limitations",
"### Licensing Information",
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"abstract = {Since the introduction of large language models in Natural Language Processing, large raw corpora have played a crucial role in Computational Linguistics. However, most of these large raw corpora are either available only for English or not available to the general public due to copyright issues. Nevertheless, there are some examples of freely available multilingual corpora for training Deep Learning NLP models, such as the OSCAR and Paracrawl corpora. However, they have quality issues, especially for low-resource languages. Moreover, recreating or updating these corpora is very complex. In this work, we try to reproduce and improve the goclassy pipeline used to create the OSCAR corpus. We propose a new pipeline that is faster, modular, parameterizable, and well documented. We use it to create a corpus similar to OSCAR but larger and based on recent data. Also, unlike OSCAR, the metadata information is at the document level. We release our pipeline under an open source license and publish the corpus under a research-only license.},",
"Papadimitriou, Isabel and"
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"Original datasets used for curation of BIGOS have specific terms of usage that must be understood and agreed to before use. Below are the links to the license terms and datasets the specific license type applies to:",
"* [Creative Commons 0](https://creativecommons.org/share-your-work/public-domain/cc0) which applies to [Common Voice](https://huggingface.co/datasets/mozilla-foundation/common_voice_13_0)",
"* [Creative Commons By Attribution Share Alike 4.0](https://creativecommons.org/licenses/by-sa/4.0/), which applies to [Clarin Cyfry](https://clarin-pl.eu/dspace/handle/11321/317), [Azon acoustic speech resources corpus](https://zasobynauki.pl/zasoby/korpus-nagran-probek-mowy-do-celow-budowy-modeli-akustycznych-dla-automatycznego-rozpoznawania-mowy,53293/).",
"* [Creative Commons By Attribution 3.0](https://creativecommons.org/licenses/by/3.0/), which applies to [CLARIN Mobile database](https://clarin-pl.eu/dspace/handle/11321/237), [CLARIN Studio database](https://clarin-pl.eu/dspace/handle/11321/236), [PELCRA Spelling and Numbers Voice Database](http://pelcra.pl/new/snuv) and [FLEURS dataset](https://huggingface.co/datasets/google/fleurs)",
"* [Creative Commons By Attribution 4.0](https://creativecommons.org/licenses/by/4.0/), which applies to [Multilingual Librispeech](https://huggingface.co/datasets/facebook/multilingual_librispeech) and [Poly AI Minds 14](https://huggingface.co/datasets/PolyAI/minds14)",
"* [Proprietiary License of Munich AI Labs dataset](https://www.caito.de/2019/01/03/the-m-ailabs-speech-dataset)",
"* Public domain mark, which applies to [PWR datasets](https://www.ii.pwr.edu.pl/~sas/ASR/)",
"I hereby confirm that I have read and accepted the license terms of datasets comprising BIGOS corpora: checkbox",
"- [Other Known Limitations](#other-known-limitations)",
"- [Licensing Information](#licensing-information)"
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