WordNet is an online lexical database designed for use under program control, aiming to provide a more effective combination of traditional lexicographic information and modern computing. It organizes English nouns, verbs, adjectives, and adverbs into sets of synonyms, each representing a lexicalized concept, and links these sets through semantic relations to determine word definitions. The database contains over 118,000 different word forms and more than 90,000 different word senses, with approximately 17% of words being polysemous and 40% having one or more synonyms. WordNet respects syntactic categories such as noun, verb, adjective, and adverb, and accommodates inflectional morphology but does not explicitly recognize derivational and compound morphology. It includes various semantic relations like synonymy, hypernymy, meronymy, and holonymy, represented by pointers between word forms or synsets. The database aims to support sense identification in natural language processing tasks, but further development is needed to fully address polysemy. Contextual representations and semantic concordances are being developed to improve sense identification accuracy.WordNet is an online lexical database designed for use under program control, aiming to provide a more effective combination of traditional lexicographic information and modern computing. It organizes English nouns, verbs, adjectives, and adverbs into sets of synonyms, each representing a lexicalized concept, and links these sets through semantic relations to determine word definitions. The database contains over 118,000 different word forms and more than 90,000 different word senses, with approximately 17% of words being polysemous and 40% having one or more synonyms. WordNet respects syntactic categories such as noun, verb, adjective, and adverb, and accommodates inflectional morphology but does not explicitly recognize derivational and compound morphology. It includes various semantic relations like synonymy, hypernymy, meronymy, and holonymy, represented by pointers between word forms or synsets. The database aims to support sense identification in natural language processing tasks, but further development is needed to fully address polysemy. Contextual representations and semantic concordances are being developed to improve sense identification accuracy.