Montenegrin web corpus CLASSLA-web.cnr 1.0

Name: Montenegrin web corpus CLASSLA-web.cnr 1.0
License: https://creativecommons.org/publicdomain/zero/1.0/

Ljubešić, Nikola; Rupnik, Peter; Kuzman, Taja

Montenegrin web corpus CLASSLA-web.cnr 1.0

CLARIN.SI data & tools

Avtorji: Ljubešić, Nikola ; Rupnik, Peter and Kuzman, Taja

Identifikator vnosa: http://hdl.handle.net/11356/1930

URL projekta: https://www.clarin.si/info/k-centre/

Demo URL: https://www.clarin.si/info/k-centre/classla-web-bigger-and-better-web-corpora-for-croatian-serbian-and-slovenian-on-clarin-si-concordancers/

Dokumentirano v: https://arxiv.org/abs/2403.12721

Datum objave: 2024-03-26

Vrsta: corpus, text

Velikost: 176987739 tokens, 150672975 words, 401290 texts

Jezik(i): Montenegrin

Opis: The Montenegrin web corpus CLASSLA-web.cnr 1.0 is based on the MaCoCu-cnr 1.0 web corpus crawl (http://hdl.handle.net/11356/1809), which was additionally cleaned and enriched with linguistic and genre information. The CLASSLA-web.cnr corpus is a part of the South Slavic CLASSLA-web corpus collection, which is the first collection of comparable corpora that encompasses the entire South Slavic language group. The MaCoCu-cnr 1.0 crawl was built by crawling the ".me" internet top-level domain in 2021 and 2022, as well as extending the crawl dynamically to other domains. During the development of CLASSLA-web corpora, the MaCoCu web crawls were cleaned by removing paragraphs that are not in the target language, and by removing very short texts (less than 75 words or consisting only of paragraphs shorter than 70 characters). The corpus was also linguistically annotated with the CLASSLA-Stanza pipeline (https://github.com/clarinsi/classla). The linguistic processing involved tokenization, morphosyntactic annotation, and lemmatization. Additionally, the corpus was automatically annotated with genres using the Transformer-based X-GENRE classifier (https://huggingface.co/classla/xlm-roberta-base-multilingual-text-genre-classifier). The following genre categories are used: News, Information/Explanation, Promotion, Opinion/Argumentation, Instruction, Legal, Prose/Lyrical, Forum, Other and Mix. The corpus is available in vertical format, as used by Sketch Engine and CWB concordancers. Information is provided on the text-, paragraph-, sentence- and token-level. Each text is accompanied by the following metadata: text id, title, url, domain, top-level domain (tld, e.g., "com"), and predicted genre category. Each text is divided into paragraphs that are accompanied by the following metadata: paragraph id, the automatically identified language of the text in the paragraph, and paragraph quality. For quality, labels, such as "short" or "good" are assigned based on paragraph length, URL and stopword density via the jusText tool (https://corpus.tools/wiki/Justext). Paragraphs are further divided into sentences that have as metadata their sentence id. Inside sentences, tokens are provided in tabular format with their linguistic annotation. Details about the structural and positional attributes are also given in the accompanying registry file which was used to install the corpus on the CLARIN.SI concordancers. Notice and take down: Should you consider that our data contains material that is owned by you and should therefore not be reproduced here, please: (1) Clearly identify yourself, with detailed contact data such as an address, telephone number or email address at which you can be contacted. (2) Clearly identify the copyrighted work claimed to be infringed. (3) Clearly identify the material that is claimed to be infringing and information reasonably sufficient in order to allow us to locate the material. (4) Please write to the contact person for this resource whose email is available in the full item record. We will comply with legitimate requests by removing the affected sources from the next release of the corpus. A JSONL version of the corpus is available as part of the MaCoCu-Genre corpora collection at http://hdl.handle.net/11356/1969. The MaCoCu-Genre version comprises texts and metadata at the text level, including genre information, and is not linguistically annotated.