Datasets:

proxectonos
/

corpusnos

pretty_name: CorpusNÓS v.3.0
language:
  - gl
license: other
task_categories:
  - text-generation
task_ids:
  - language-modeling
tags:
  - galician
  - corpus
  - language-modeling
  - pretraining
  - jsonl
  - web-corpus
  - ocr
  - low-resource-nlp
size_categories:
  - 1M<n<10M
configs:
  - config_name: public_data_encyclopedic
    data_files:
      - split: train
        path:
          - public_data/encyclopedic/*.jsonl
          - public_data/encyclopedic/**/*.jsonl
  - config_name: public_data_press_and_blogs
    data_files:
      - split: train
        path:
          - public_data/press_and_blogs/*.jsonl
          - public_data/press_and_blogs/**/*.jsonl
  - config_name: public_data_translation_corpora
    data_files:
      - split: train
        path:
          - public_data/translation_corpora/*.jsonl
          - public_data/translation_corpora/**/*.jsonl
  - config_name: public_data_web_crawls
    data_files:
      - split: train
        path:
          - public_data/web_crawls/*.jsonl
          - public_data/web_crawls/**/*.jsonl
  - config_name: dta_books
    data_files:
      - split: train
        path:
          - data_transfer_agreement/books/*.jsonl
          - data_transfer_agreement/books/**/*.jsonl
  - config_name: dta_encyclopedic
    data_files:
      - split: train
        path:
          - data_transfer_agreement/encyclopedic/*.jsonl
          - data_transfer_agreement/encyclopedic/**/*.jsonl
  - config_name: dta_governmental
    data_files:
      - split: train
        path:
          - data_transfer_agreement/governmental/*.jsonl
          - data_transfer_agreement/governmental/**/*.jsonl
  - config_name: dta_press_and_blogs
    data_files:
      - split: train
        path:
          - data_transfer_agreement/press_and_blogs/*.jsonl
          - data_transfer_agreement/press_and_blogs/**/*.jsonl
  - config_name: dta_research_articles
    data_files:
      - split: train
        path:
          - data_transfer_agreement/research_articles/*.jsonl
          - data_transfer_agreement/research_articles/**/*.jsonl
  - config_name: dta_web_contents
    data_files:
      - split: train
        path:
          - data_transfer_agreement/web_contents/*.jsonl
          - data_transfer_agreement/web_contents/**/*.jsonl

CorpusNÓS v.3.0

Dataset description

CorpusNÓS is a massive Galician corpus primarily devised for training large language models. It is composed of texts from a wide range of sources and genres, including books, research articles, press, governmental texts, encyclopedic data, web contents, web crawls, blogs, and translation corpora.

This release corresponds to an updated JSONL-based version of the corpus. Compared with previous releases, this version incorporates improvements in the text cleaning and processing pipeline, stronger deduplication, improved OCR for materials originating from PDF sources, and the reprocessing of part of the data in order to improve overall quality.

Unlike earlier releases, this version is distributed only in JSONL format. Each document is represented as an individual JSON object, which facilitates downstream filtering, cleaning, and metadata enrichment.

Some newly incorporated data from Praza Pública, Diario Nós and Wikipedia are also included in this version. These sources are expected to be extended in future releases as more material is processed.

Dataset format

Each document is stored as a JSON object in JSONL format. Typical entries may have the following structure:

{"id": 0, "text": "Abades: Parroquia do concello de Baltar baixo a advocación de san Paio.", "num_words": 12}
{"id": 581, "text": "Feliz 2008 a tódolos nosos lectores\nAgora que remata 2007, un ano cheo de novidades tecnolóxicas que difundimos a través deste espazo dixital, queremos desexar a tódolos que non seguen con fidelidade unha boa despedida do ano e un feliz aninovo.\nNós volveremos o mércores, 2 de xaneiro, á nosa actividade ordinaria, cumprindo coa nosa labor informativa para que as novas tecnolóxicas de Galicia e en galego cheguen ós nosos lectores puntualmente.", "num_words": 72, "pyplexity_score": 717.7585757844212, "lang": "gl"}

The core fields are:

id: document identifier
text: textual content of the document
num_words: number of words in the document

Some entries may also include additional metadata such as:

pyplexity_score
lang

Differences from previous versions

This version differs from earlier releases in several ways:

It includes improvements in the text cleaning and processing pipeline
It includes improved OCR for files originating from PDF sources
It includes reprocessed data to improve quality
It incorporates new data from Praza Pública and Diario Nós, which will be expanded in future versions
It includes a cleaner and updated version of Galician Wikipedia data, which will be expanded in future versions

Dataset composition

The corpus is organized into two major subcorpora:

Data obtained via transfer agreement
Public data

Data source and creation

CorpusNÓS was compiled from multiple heterogeneous sources in Galician and related multilingual resources relevant to language model training. The corpus combines public data and data made available through transfer agreements.

This version was created through an updated processing pipeline that includes:

improved text cleaning
stronger deduplication
improved OCR for PDF-derived materials
reprocessing of selected resources to improve quality
conversion and standardization into JSONL format

The aim of this release is to provide a cleaner, more structured, and more easily processable corpus for large-scale language modeling and related NLP tasks in Galician.

Current statistics

Subcorpus: Data obtained via transfer agreement

Genre	Nº tokens	Nº documents
Books	7,074,354	103
Research articles	3,005,739	499
Press and blogs	98,086,871	204,598
Governmental	260,333,471	408,607
Web contents	15,390,104	41,276
Encyclopedic	4,799,208	47,396
Subtotal	388,689,747	702,479

Subcorpus: Public data

Genre	Nº tokens	Nº documents
Press and blogs	142,144,734	598,375
Encyclopedic	75,630,525	226,964
Web crawls	1,205,208,148	2,850,604
Translation corpora	105,523,634	3,544,025
Subtotal	1,528,507,041	7,219,968

Total

Total tokens	Total documents
1,917,196,788	7,922,447

Intended uses

This dataset can be used for:

continued pretraining of language models in Galician
corpus-based analysis of Galician text
low-resource NLP research
multilingual and cross-lingual experiments involving Galician
data selection, filtering, and quality analysis for LLM training

Limitations

Some files referenced in the corpus may still be absent in this version due to pending transfer agreements and may be included in future releases. Other files might be unavailable due to licensing issues.
The corpus contains materials from heterogeneous sources and genres, which implies variation in style, register, and quality.
Although this version includes stronger cleaning, deduplication, OCR improvement, and reprocessing, some noise may still remain.
Some subcorpora are subject to their original licenses and restrictions.

Licensing

This dataset includes materials under different licenses depending on the original source. Please refer to the original source licenses.

In particular, the following subcorpora retain their original licenses:

TED2020: CC BY-NC-ND 4.0
mC4: Apache License 2.0
OSCAR: CC0

All other subcorpora that do not have a previously established original license are released under CC BY-SA 4.0.

Users are responsible for checking the license conditions of each subcorpus before use.

Citation

Please refer to our paper for more details:

@inproceedings{de-dios-flores-etal-2024-corpusnos,
    title = "{C}orpus{N{\'O}S}: A massive {G}alician corpus for training large language models",
    author = "de-Dios-Flores, Iria  and
      Su{\'a}rez, Silvia Paniagua  and
      P{\'e}rez, Cristina Carbajal  and
      Outeiri{\~n}o, Daniel Bardanca  and
      Garcia, Marcos  and
      Gamallo, Pablo",
    editor = "Gamallo, Pablo  and
      Claro, Daniela  and
      Teixeira, Ant{\'o}nio  and
      Real, Livy  and
      Garcia, Marcos  and
      Oliveira, Hugo Gon{\c{c}}alo  and
      Amaro, Raquel",
    booktitle = "Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1",
    month = mar,
    year = "2024",
    address = "Santiago de Compostela, Galicia/Spain",
    publisher = "Association for Computational Lingustics",
    url = "https://aclanthology.org/2024.propor-1.66/",
    pages = "593--599"
}

Acknowledgements

This corpus was compiled and developed within the Nós Project, funded by the Ministerio para la Transformación Digital y de la Función Pública and by the European Union through NextGenerationEU, within the framework of the ILENIA project (reference 2022/TL22/00215336).