gaTenTen: Corpus of the Irish Web
The Irish Web Corpus (gaTenTen) is an Irish corpus made up of texts collected from the Internet. The corpus belongs to the TenTen corpus family. Sketch Engine currently provides access to TenTen corpora in more than 40 languages. The corpora are built using technology specialized in collecting only linguistically valuable web content. The Irish language (in Standard Irish “Gaeilge”) is also known as Irish Gaelic.
For detailed information about TenTen corpora, see Common TenTen corpora attributes.
The Irish Web corpus 2022 consists of:
- the Irish web (downloaded in November 2017, January–March 2021, and October 2022),
- Wikipedia articles from 2022,
- and Irish EUR-Lex 2016 (an official website of European Union law)
in the total size of 125 million words.
The sample texts of the biggest web domains which account for 55% of all corpus texts were checked semi-manually and content with poor-quality text and spam was removed.
Part-of-speech tagset
The gaTenTen Irish corpus is tagged by the RFTagger trained on Irish Universal Dependencies Treebank, lemmatized using Irish National Morphology Database (without manual corrections). The corpus uses the Universal Dependencies tags for Irish including morphological features.
Search the Irish corpus gaTenTen
Sketch Engine offers a range of tools to work with this Gaelic corpus.
Genre annotation and topic classification
The Irish Web 2022 corpus contains genre annotation and topic classification that can be displayed as corpus structures. Genres refer to writing styles and are divided into four groups (blog, legal, news) whereas topic classification is inspired by categories used by https://curlie.org/ (formerly dmoz.org) and includes the following topics: arts, computers, economy & finance & business, education, history, news, politics & government, reference, regional, science, shopping, and society.
- genres cover 33.1% of the corpus, i.e. 47.6 million tokens
- topic classification covers 31.4% of the corpus, i.e. 45.1 million tokens
Hover over the chart to display a number of tokens of the particular topic.
Hover over the chart to display a number of tokens of the particular topic.
Basic frequency statistics of the Irish Web 2022 corpus
Frequency | |
Tokens | 143,794,407 |
Words | 125,040,541 |
Sentences | 5,840,868 |
Web pages | 298,869 |
Tools to work with the Irish corpus from the web
A complete set of Sketch Engine tools is available to work with this Irish corpus to generate:
- word sketch – Irish collocations categorized by grammatical relations
- thesaurus – synonyms and similar words for every word
- keywords – terminology extraction of one-word units
- word lists – lists of English nouns, verbs, adjectives etc. organized by frequency
- n-grams – frequency list of multi-word units
- concordance – examples in context
- text type analysis – statistics of metadata in the corpus
Bibliography
TenTen corpora
SUCHOMEL, Vít. Better Web Corpora For Corpus Linguistics And NLP. 2020. Available also from: https://is.muni.cz/th/u4rmz/. Doctoral thesis. Masaryk University, Faculty of Informatics, Brno. Supervised by Pavel RYCHLÝ.
Jakubíček, M., Kilgarriff, A., Kovář, V., Rychlý, P., & Suchomel, V. (2013, July). The TenTen corpus family. In 7th International Corpus Linguistics Conference CL (pp. 125-127).
Suchomel, V., & Pomikálek, J. (2012). Efficient web crawling for large text corpora. In Proceedings of the seventh Web as Corpus Workshop (WAC7) (pp. 39-43).
Universal Dependencies for Irish
Lynn, Teresa and Jennifer Foster. Universal Dependencies for Irish. In Proceedings of CLTW 2016. Paris, France, July 2016.
Irish National Morphology Database
Měchura, Michal Boleslav. Irish National Morphology Database: a high-accuracy open-source dataset of Irish words. In Proceedings of the First Celtic Language Technology Workshop (pp. 50-54) at CoLing. Dublin, Ireland. 2014.
Genre annotation
SUCHOMEL, Vít. Genre Annotation of Web Corpora: Scheme and Issues. In Kohei Arai, Supriya Kapoor, Rahul Bhatia. Proceedings of the Future Technologies Conference (FTC) 2020, Volume 1. Vancouver, Canada: Springer Nature Switzerland AG, 2021. s. 738-754. ISBN 978-3-030-63127-7. doi:10.1007/978-3-030-63128-4_55.
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