Update README.md

README.md

@@ -1,7 +1,8 @@
 ---
+pretty_name: CorpusNÓS v.3.0
 language:
   - gl
-license: cc-by-sa-4.0
+license: other
 task_categories:
   - text-generation
 task_ids:
@@ -14,9 +15,9 @@ tags:
   - jsonl
   - web-corpus
   - ocr
+  - low-resource-nlp
 size_categories:
   - 1M<n<10M
-pretty_name: CorpusNÓS v.3.0
 configs:
   - config_name: public_data_encyclopedic
     data_files:
@@ -87,4 +88,131 @@ configs:
         path:
           - data_transfer_agreement/web_contents/*.jsonl
           - data_transfer_agreement/web_contents/**/*.jsonl
----
+---
+
+# CorpusNÓS v3 2026
+
+## 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:
+
+```json
+{"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.
+
+## 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:
+
+```bibtex
+@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](https://proyectoilenia.es/) (reference 2022/TL22/00215336).