MLRS/korpus_malti

Korpus Malti 🇲🇹

General Corpora for the Maltese Language.

This dataset is composed of texts from various genres/domains written in Maltese.

Versions

This dataset is updated from time to time, and the latest version is obtained unless otherwise specified. Consult the changelog for a detailed overview of each version released.

If you want to fetch a particular version, use the revision argument. For example, to get the data used to train BERTu, use the 4.0.0 tag:

import datasets

dataset = datasets.load_dataset("MLRS/korpus_malti", revision="4.0.0")

Configurations

Shuffled data

The default configuration ("shuffled") yields the entire corpus from all genres:

import datasets

dataset = datasets.load_dataset("MLRS/korpus_malti")

All sentences are combined together and shuffled, without preserving the sentence order. No other annotations are present, so an instance would be of the following form:

{
  "text": "Din hija sentenza."
}

Domain-split data

All other configurations contain a subset of the data. The available data subsets are:

• belles_lettres: Literary texts, usually published and included in the corpus by permission of the copyright holder. Unfortunately these cannot be disseminated in their integral form.
• blogs: Online blog articles from specific blogs, identified in advance and known to contain text written (or human-translated into) Maltese.
• comics: A small set of online information about comic books in Maltese.
• court: Publicly available proceedings form the courts of Malta.
• eu_docs: Miscellaneous policy documents from the European Union institutions.
• gov_docs: Miscellaneous policy documents from the Government of Malta.
• government_gazzette: The official, publicly available gazette of the Government of Malta. The gazzette is bilingual; only the Maltese text is included.
• law_eu: Miscellaneous EU laws in their official Maltese translation, obtained via the Eur-Lex repository and including the segments of the Acquis Communautaire available in the DGT translation memory.
• law_mt: Maltese laws.
• legal: Miscellaneous legal text.
• nonfiction: Miscellaneous nonfiction, published or unpublished. Published texts are included with the permission of the copyright holder, where relevant.
• parliament: The officially released transcripts of parliamentary debates of the Maltese parliament.
• press_eu: Press releases in Maltese by the European Council of Ministers, European Parliament and European Commission.
• press_mt: Articles in the Maltese press, sourced primarily from the online portals of Maltese newspapers.
• speeches: Miscellaneous speeches in Maltese (pre-written).
• theses: Academic dissertations written in Maltese.
• umlib_oar: Very broad variety of nonfiction texts which are publicly available in the University of Malta Open Access Repository. Included with help and permission from the University of Malta library.
• web_general: Miscellaneous text scraped from pre-identified web pages in Maltese.
• wiki: The Maltese Wikipedia dump (downloaded 26th May, 2020).

For instance, this loads the Wikipedia portion:

import datasets

dataset = datasets.load_dataset("MLRS/korpus_malti", "wiki")

For these configurations the data is not shuffled, so the sentence order on a document level is preserved. An instance from these configurations would take the following form:

{
  "text": ["Din hija sentenza.", "U hawn oħra!"],
  ...
}

The instances also contain additional metadata. Their structure differs from one instance to another, depending on what's available from the source. This information was typically scraped from the source itself & minimal processing is performed on such data.

Additional Information

Dataset Curators

The dataset was created by Albert Gatt, Kurt Micallef, Marc Tanti, Lonneke van der Plas and Claudia Borg.

Licensing Information

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Permissions beyond the scope of this license may be available at https://mlrs.research.um.edu.mt/.

Citation Information

This work was first presented in Pre-training Data Quality and Quantity for a Low-Resource Language: New Corpus and BERT Models for Maltese. Cite it as follows:

@inproceedings{BERTu,
    title = "Pre-training Data Quality and Quantity for a Low-Resource Language: New Corpus and {BERT} Models for {M}altese",
    author = "Micallef, Kurt  and
              Gatt, Albert  and
              Tanti, Marc  and
              van der Plas, Lonneke  and
              Borg, Claudia",
    booktitle = "Proceedings of the Third Workshop on Deep Learning for Low-Resource Natural Language Processing",
    month = jul,
    year = "2022",
    address = "Hybrid",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.deeplo-1.10",
    doi = "10.18653/v1/2022.deeplo-1.10",
    pages = "90--101",
}