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For example, a word can have several word senses. [3] Polysemy is distinct from monosemy, where a word has a single meaning. [3] Polysemy is distinct from homonymy—or homophony—which is an accidental similarity between two or more words (such as bear the animal, and the verb bear); whereas homonymy is a mere linguistic coincidence, polysemy ...
Semantic properties or meaning properties are those aspects of a linguistic unit, such as a morpheme, word, or sentence, that contribute to the meaning of that unit.Basic semantic properties include being meaningful or meaningless – for example, whether a given word is part of a language's lexicon with a generally understood meaning; polysemy, having multiple, typically related, meanings ...
In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]
In linguistics, a word sense is one of the meanings of a word. For example, a dictionary may have over 50 different senses of the word "play", each of these having a different meaning based on the context of the word's usage in a sentence, as follows: We went to see the play Romeo and Juliet at the theater.
Componential analysis is a method typical of structural semantics which analyzes the components of a word's meaning. Thus, it reveals the culturally important features by which speakers of the language distinguish different words in a semantic field or domain (Ottenheimer, 2006, p. 20).
Pages in category "Polysemy" The following 8 pages are in this category, out of 8 total. This list may not reflect recent changes. ...
A monosemous analysis assumes that any sign in a sign system signals one value within its paradigm, with a substance that arises out of its diachronic history. [ 5 ] There are some cases where a word genuinely has two meanings that cannot be brought under a singular, more abstract sense, but these are better understood as instances of homonymy .
For each context window, MSSA calculates the centroid of each word sense definition by averaging the word vectors of its words in WordNet's glosses (i.e., short defining gloss and one or more usage example) using a pre-trained word-embedding model. These centroids are later used to select the word sense with the highest similarity of a target ...