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Text corpora (singular: text corpus) are large and structured sets of texts, which have been systematically collected.Text corpora are used by both AI developers to train large language models and corpus linguists and within other branches of linguistics for statistical analysis, hypothesis testing, finding patterns of language use, investigating language change and variation, and teaching ...
The Corpus of Contemporary American English (COCA) is composed of one billion words as of November 2021. [1] [2] [4] The corpus is constantly growing: In 2009 it contained more than 385 million words; [5] in 2010 the corpus grew in size to 400 million words; [6] by March 2019, [7] the corpus had grown to 560 million words.
View a machine-translated version of the Japanese article. Machine translation, like DeepL or Google Translate, is a useful starting point for translations, but translators must revise errors as necessary and confirm that the translation is accurate, rather than simply copy-pasting machine-translated text into the English Wikipedia.
(August 2021) Click [show] for important translation instructions. View a machine-translated version of the Japanese article. Machine translation, like DeepL or Google Translate , is a useful starting point for translations, but translators must revise errors as necessary and confirm that the translation is accurate, rather than simply copy ...
Machine translation algorithms for translating between two languages are often trained using parallel fragments comprising a first-language corpus and a second-language corpus, which is an element-for-element translation of the first-language corpus. [3] Philologies
The Meiji-era Classical Japanese version of the Bible renders Jehovah as ヱホバ (Yehoba), and ヱ (ye) is also used to transcribe any Hebrew name spelled with Je in English (pronounced "ye" in Hebrew, though), such as Jephthah (ヱフタ, Yefuta); the modern Japanese version, on the other hand, only uses エ (e), hence エホバ (Ehoba) and ...
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View a machine-translated version of the Japanese article. Machine translation, like DeepL or Google Translate, is a useful starting point for translations, but translators must revise errors as necessary and confirm that the translation is accurate, rather than simply copy-pasting machine-translated text into the English Wikipedia.