korpusová

Korpusové is a Czech adjective meaning "corpus-based" and is used to describe methods, data, and findings in corpus linguistics. In English-language literature, the term is typically rendered as "corpus-based" or "corpus-driven". The concept centers on the analysis of authentic language data drawn from large collections of texts, known as corpora, to understand linguistic patterns and usage.

Definition and scope: Corpus-based approaches rely on annotated or raw text corpora rather than solely on introspection. Data can be monolingual or multilingual and may include various genres. Researchers extract frequency information, concordances, collocations, and lexical bundles; they may also perform statistical analysis to identify significant patterns.

Workflow and tools: Building a corpus involves collection, cleaning, and normalization. Annotation may include tokenization, lemmatization, part-of-speech tagging, and syntactic parsing. Querying and visualization tools produce frequency lists, concordance lines, and collocation networks. Common measures include mutual information and t-scores for collocate strength.

Applications: Korpusové methods inform lexicography, grammar description, language teaching, translation studies, and sociolinguistics. They underpin corpus-based dictionaries, grammar resources, and natural language processing tools such as part-of-speech taggers and parsers. They are also used in diachronic studies to track changes in usage over time.

Examples and issues: In Czech linguistics, notable corpora include the Czech National Corpus (CNC) and the Prague Dependency Treebank (PDT). While powerful, corpus-based research depends on data representativeness, licensing, and annotation quality, and results may reflect corpus biases toward particular genres or registers.