WN

wn is a common abbreviation for WordNet, a large lexical database of the English language. WordNet organizes English words into sets of cognitive synonyms called synsets, each representing a single lexical concept. Each synset includes short definitions and usage examples, and words can be linked across synsets by semantic relations. WordNet is widely used in natural language processing and linguistics as a resource for measuring semantic similarity, performing word sense disambiguation, and supporting information retrieval and machine translation tasks.

The core data model of WordNet consists of synsets, lemmas (word forms), and relations between synsets. Key relations include hypernymy and hyponymy (conceptual hierarchy), meronymy and holonymy (part-whole relationships), and various derivational and antonym connections. Word senses are often disambiguated by context, and the same lemma can occur in multiple synsets corresponding to different senses. In addition to noun and verb synsets, WordNet also covers adjectives and adverbs, sometimes with distinct organizational structures.

WordNet has played a foundational role in computational linguistics and NLP since its development at Princeton University in the 1980s and 1990s. The resource is distributed with licenses that allow broad use in research and many commercial applications. Its data model supports multilingual extensions through Open Multilingual WordNets, which align WordNet-like structures for multiple languages.

The term wn also refers to software interfaces that provide programmatic access to WordNet data. Notable implementations include libraries that enable searching for synsets, exploring semantic relations, and retrieving definitions and examples from WordNet or its multilingual counterparts. These tools facilitate tasks such as lexical analysis, semantic search, and knowledge-based NLP systems.