extraction of parallel sentence pairs (e.g.Rapp 1999, Prochasson and Fung 2011, Rapp et al. extraction of bilingual dictionaries (e.g.Possible applications of the comparable corpora include Les Fleurs du mal (De bloemen van het kwaad) is de belangrijkste dichtbundel van de Franse dichter Charles Baudelaire.įlorile răului este o culegere de poezii ale poetului francez Charles Baudelaire. The content therefore includes p and h tags marking paragraphs and headings, and also links and tables (see the XML format description on the monolingual corpora page). The categories are copied from the respective Wikipedia Monolingual Corpora XML files, as is the content. Each article has a number of categories and a content. „Deep“ links that link an article to a section of a target article have been replaced by a link to the whole article (see note on crosslanguage_links in the XML format description on the monolingual corpora page). Corresponding means that both articles are linked via a crosslanguage link (in any direction). Each articlePair encloses two articles, one from the first language Wikipedia, and a corresponding one from the second language Wikipedia. The header is followed by n elements of type articlePair, which have an attribute id with a unique identification number. Their attributes give the languages and the names of the two source Wikipedia Monolingual Corpora’s XML files. Then follows a header which has two daughter nodes, both of type wikipediaSource. Its attribute name contains the language pair. The XML file’s root element is wikipediaComparable.
Language identification qwiki license#
Click on a cell to download the corpus file.īefore downloading, make sure you have read and understood the license conditions (see below). If you hover over a cell a tooltip pops up that gives the number of tokens in each of the two languages. The table cells contain the number of aligned articles for each language pair. The 253 corpus files occupy 405 GB disk space when unzipped. Alltogether, there are over 41 million aligned articles for 253 language pairs. Each comparable corpus consists of document pairs: Wikipedia articles in language L1 and the linked article in language L2 on the same subject. They have been extracted from the Wikipedia Monolingual Corpora’s XML files using the crosslanguage links. The dataset is a CSV file consisting of 1000 text samples from 22 languages each, making it a total of 22k samples sin the dataset.The Wikipedia Comparable Corpora are bilingual document-aligned text corpora. WiLI-2018, the Wikipedia language identification benchmark dataset, contains 235000 paragraphs of 235 languages.Īfter data selection and preprocessing 22 languages from the original dataset were selected to create the current dataset.Įach language in this dataset contains 1000 rows/paragraphs. Implementation of the idea on cAInvas - here! The dataset In this article, we classify text data into 22 languages - Arabic, Chinese, Dutch, English, Estonian, French, Hindi, Indonesian, Japanese, Korean, Latin, Persian, Portuguese, Pushto, Romanian, Russian, Spanish, Swedish, Tamil, Thai, Turkish, Urdu. For example, the detect language feature of Google translate detects the language of the input text before translating it. This categorization becomes important when the language of the input data is not assumed. It is a text categorization problem at its core, with the languages being the classes. Language detection refers to determining the language that the given text is written in.
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