Search results
Results from the WOW.Com Content Network
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 ...
Corpus linguistics is an empirical method for the study of language by way of a text corpus (plural corpora). [1] Corpora are balanced, often stratified collections of authentic, "real world", text of speech or writing that aim to represent a given linguistic variety. [1] Today, corpora are generally machine-readable data collections.
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 Text corpora are also used in the study of historical documents, for example ...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 Brown University Standard Corpus of Present-Day American English, better known as simply the Brown Corpus, is an electronic collection of text samples of American English, the first major structured corpus of varied genres. This corpus first set the bar for the scientific study of the frequency and distribution of word categories in ...
In order to be able to meticulously study the English language, an annotated text corpus was much needed. The Penn Treebank [ 5 ] was one of the most used corpora. It consisted of IBM computer manuals, transcribed telephone conversations, and other texts, together containing over 4.5 million words of American English, annotated using both part ...
A prominent example is probabilistic latent semantic analysis (PLSA). Latent Dirichlet allocation, which involves attributing document terms to topics. n-grams and hidden Markov models, which work by representing the term stream as a Markov chain, in which each term is derived from preceding terms.
For example, terms A and B may be said to “co-occur” if they both appear in a particular article. 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
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):