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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 ...
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. Text corpora are also used in the study of historical documents, for example ...
The TenTen Corpus Family (also called TenTen corpora) is a set of comparable web text corpora, i.e. collections of texts that have been crawled from the World Wide Web and processed to match the same standards. These corpora are made available through the Sketch Engine corpus manager. There are TenTen corpora for more than 35 languages.
The field of corpus linguistics studies language as expressed in text corpora. This includes the analysis of word frequency, collocations, grammar, and semantics. Ancient text corpora provide a valuable resource for corpus linguistics research, enabling scholars to explore the evolution of language and culture over time.
Treebanks are necessarily constructed according to a particular grammar. The same grammar may be implemented by different file formats. For example, the syntactic analysis for John loves Mary, shown in the figure on the right/above, may be represented by simple labelled brackets in a text file, like this (following the Penn Treebank notation):
Another article may contain terms B and C. Linking A to B and B to C creates a co-occurrence network of these three terms. Rules to define co-occurrence within a text corpus can be set according to desired criteria. For example, a more stringent criteria for co-occurrence may require a pair of terms to appear in the same sentence.
The Bank of English (BoE) is a representative subset of the 4.5 billion words COBUILD corpus, a collection of English texts.These are mainly British in origin, but content from North America, Australia, New Zealand, South Africa and other Commonwealth countries is also being included.
Text-to-image models are trained on large datasets of (text, image) pairs, often scraped from the web. With their 2022 Imagen model, Google Brain reported positive results from using a large language model trained separately on a text-only corpus (with its weights subsequently frozen), a departure from the theretofore standard approach.