Korpusdata

Korpusdata, or corpus data, is data derived from linguistic corpora—structured collections of authentic language samples used for linguistic analysis and natural language processing. A corpus may be monolingual or multilingual and include written or spoken material, along with annotations and metadata that describe content and provenance.

Korpusdata typically comprises text, linguistic annotations, and metadata. Annotations may include tokens, lemmas, part-of-speech tags, morphological features, and syntactic or semantic labels. Data are stored in formats such as plain text, XML/TEI, JSON, or CoNLL-U, with metadata on language, domain, and licensing.

Collection involves compiling sources like books, newspapers, academic corpora, web data, or speech transcripts. Copyright, licensing, and access restrictions apply, and provenance must be documented. When personal data are present, privacy-preserving practices such as anonymization and consent management are commonly observed.

Annotation and processing use manual and automatic methods to create high-quality data. Validation includes inter-annotator agreement, consistency checks, and gold-standard benchmarks to support reproducible research and reliable NLP model training.

Applications include linguistic research, lexicography, language documentation, and the development and evaluation of NLP systems. Korpusdata supports cross-linguistic comparison, corpus-based reasoning, and benchmarking, enabling researchers and developers to study language patterns and build language-aware technologies.

Standards and repositories promote interoperability and access. Common formats include TEI and CoNLL-U; data are shared via archives such as CLARIN, ELDA/LDC, or university repositories, with licensing and ethical guidelines guiding responsible use of corpus resources.