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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.
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 table also includes frequencies from other corpora. As well as usage differences, lemmatisation may differ from corpus to corpus – for example splitting the prepositional use of "to" from the use as a particle. Also, the Corpus of Contemporary American English (COCA) list includes dispersion as well as frequency to calculate rank.
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
[1] [2] [5] There are also some specialized English corpora, such as American English, British English, and English Fiction. [6] The program can search for a word or a phrase, including misspellings or gibberish. [5] The n-grams are matched with the text within the selected corpus, and if found in 40 or more books, are then displayed as a graph ...
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In corpus linguistics, a text corpus is a large and structured collection of texts that are electronically stored and processed. It is used to do hypothesis testing about languages, validating linguistic rules or the frequency distribution of words ( n-grams ) within languages.
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