vocabulariesclean
Vocabulariesclean is a term used in natural language processing and digital humanities to refer to the process, toolkit, or framework for cleaning and standardizing vocabulary lists and lexical resources. The aim is to improve consistency, interoperability, and traceability of terms across datasets by removing duplicates, normalizing spellings, mapping variants to a canonical form, and capturing provenance data.
Key features commonly associated with vocabulariesclean include normalization procedures such as case folding, diacritic handling, stemming
Data models used in vocabulariesclean typically represent terms with fields such as id, term, lemma, part of
Common use cases include lexicon curation for NLP applications, ontology alignment, terminology management in digital libraries,
See also: controlled vocabulary, lexical normalization, ontology alignment, data provenance.