WordNet2.0 datamodel, version 7. This ontology is an attempt to encode part of the WordNet 2.0 datamodel into OWL. It is part of the work made by the WNET Task Force of the SWBPD Working Group of W3C. First version has been edited by Guus Schreiber, then revised by Brian McBride. Current version (4) has been enlarged, commented, and checked after the original WordNet specifications by Aldo Gangemi. V5: Minor adaptations/additions for RDFS/OWL compatibility by Mark van Assem. Changes from V5 to V6 of the datamodel: added some missing inverse properties, added owl:SymmetricProperty for wn:sameVerbGroupAs, wn:derivationallyRelated. Removed two nameless classes. V6 to V7: added class AdjectiveSatelliteWordSense. From WordNet documentation (http://wordnet.princeton.edu/man/wngloss.7WN): Information in WordNet is organized around logical groupings called synsets. Each synset consists of a list of synonymous words or collocations (eg. "fountain pen" , "take in" ), and pointers that describe the relations between this synset and other synsets. A word or collocation may appear in more than one synset, and in more than one part of speech. The words in a synset are logically grouped such that they are interchangeable in some context. Two kinds of relations are represented by pointers: lexical and semantic. Lexical relations hold between word forms; semantic relations hold between word meanings. These relations include (but are not limited to) hypernymy/hyponymy, antonymy, entailment, and meronymy/holonymy. Nouns and verbs are organized into hierarchies based on the hypernymy/hyponymy relation between synsets. Additional pointers are be used to indicate other relations. Adjectives are arranged in clusters containing head synsets and satellite synsets. Each cluster is organized around antonymous pairs (and occasionally antonymous triplets). The antonymous pairs (or triplets) are indicated in the head synsets of a cluster. Most head synsets have one or more satellite synsets, each of which represents a concept that is similar in meaning to the concept represented by the head synset. One way to think of the adjective cluster organization is to visualize a wheel, with a head synset as the hub and satellite synsets as the spokes. Two or more wheels are logically connected via antonymy, which can be thought of as an axle between the wheels. Pertainyms are relational adjectives and do not follow the structure just described. Pertainyms do not have antonyms; the synset for a pertainym most often contains only one word or collocation and a lexical pointer to the noun that the adjective is "of or pertaining to". Participial adjectives have lexical pointers to the verbs that they are derived from. Adverbs are often derived from adjectives, and sometimes have antonyms; therefore the synset for an adverb usually contains a lexical pointer to the adjective from which it is derived. 1 A meaning of a word in WordNet. Each sense of a word is in a different synset. Each word sense is contained in exactly one synset. ****************************** Word and WordSenses are distinguished in this datamodel for two reasons: 1) WordNet uses the distinction in the database, and several relations are defined for WordSenses rather than for Synsets. 2) For the sake of ontological clarity, here it is assumed that synsets include word senses, in order to partition the logical space of the lexicon (words as forms, which belong to different natural language lexica, words as meanings, which also can be peculiar to different natural languages, but usually exist in several of them, and synsets, which cluster word senses by abstracting out their distributional context. ****************************** 1 A sense of an adjective satellite word. 1 A sense of an adjective word. A synset including adverb word senses. A Synset in an adjective cluster representing a concept that is similar in meaning to the concept represented by its head synset . A collocation in WordNet is a string of two or more words, connected by spaces or hyphens. Examples are: man-eating shark , blue-collar , depend on , line of products . In the database files spaces are represented as underscore (_ ) characters. Any word or composed term (collocation) deputed to have a sense in WordNet. ****For the sake of ontological clarity, here it is assumed that synsets include word senses, in order to partition the logical space of the lexicon (words as forms, which belong to different natural language lexica, words as meanings, which also can be peculiar to different natural languages, but usually exist in several of them, and synsets, which cluster word senses by abstracting out their distributional context.**** 1 A meaning of an adverb word. A synset including noun word senses. A synset including verb word senses. 1 A meaning of a verb word. 1 A meaning of a noun word. A synset including adjective word senses. A synonym set; a set of words that are interchangeable in some context. ****************************** Word and WordSenses are distinguished in this datamodel for two reasons: 1) WordNet uses the distinction in the database, and several relations are defined for WordSenses rather than for Synsets. 2) For the sake of ontological clarity, here it is assumed that Synsets include word senses, in order to partition the logical space of the lexicon (words as forms, which belong to different natural language lexica, words as meanings, which also can be peculiar to different natural languages, but usually exist in several of them, and synsets, which cluster word senses by abstracting out their distributional context. ****************************** It specifies that the second synset is a substance meronym of the first synset. This relation only holds for nouns. It specifies that the second synset is a member meronym of the first synset. This relation only holds for nouns. ****A relation added here to link words and word senses explicitly (in the WordNet db, it is implicit in the synset record)**** It specifies that the second synset is a meronym of the first synset. This relation only holds for nouns. ****A relation added here to link word senses and synsets explicitly (in the WordNet db, it is implicit in the sense tag record)**** It specifies that the second synset is a cause of the first synset. This relation only holds for verbs. It specifies that the second synset is a part meronym of the first synset. This relation only holds for nouns. It defines the attribute relation between noun and adjective synset pairs in which the adjective is a value of the noun. It specifies that the first synset has been classified as a member of the class (either as topic or 'category', as region, or as usage) represented by the second (noun) synset. It specifies that additional information about the first word can be obtained by seeing the second word. This operator is only defined for verbs and adjectives. There is no symmetric relation (ie. it cannot be inferred that the additional information about the second word can be obtained from the first word). ****A relation added here to link synsets and word senses explicitly (in the WordNet db, it is implicit in the sense tag record)**** A datatype relation between word senses and their tags within synsets. inverse of causedBy A datatype relation between synsets and their integer identifiers. noun/noun, e.g. nose/face It specifies that the second synset is similar in meaning to the first synset. This means that the second synset is a satellite of the first synset, which is the cluster head. This relation only holds for adjective synsets contained in adjective clusters. It specifies an adjective word sense that pertains to either the noun or adjective second word sense. It specifies that the adjective first word is a participle of the verb second word. ****A relation added here to link word senses and words explicitly (in the WordNet db, it is implicit in the synset record)**** It specifies an adverb word sense that pertains to the adjective second word sense. A datatype relation between Word and its lexical form. It specifies the gloss for a synset. It specifies a generic sentence frame for one or all words in a synset. The operator is defined only for verbs. A verb X entails Y if X cannot be done unless Y is, or has been, done. It specifies that the second synset is an entailment of first synset. This relation only holds for verbs. It specifies that the second synset is a hypernym of the first synset. This relation holds for nouns and verbs. The symmetric operator, hyponym, implies that the first synset is a hyponym of the second synset. It specifies that there exists a symmetric lexical morphosemantic relation between the first and second synset terms representing derivational morphology. ***In the WordNet database this relation extends over word senses within synsets*** It specifies antonymous word senses. This is a lexical relation that holds for all syntactic categories. For each antonymous pair, both relations are listed. It specifies verb synsets that are similar in meaning and should be grouped together when displayed in response to a grouped synset search.