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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 ...
Examples include the pair stalk (part of a plant) and stalk (follow/harass a person) and the pair left (past tense of leave) and left (opposite of right). A distinction is sometimes made between true homonyms, which are unrelated in origin, such as skate (glide on ice) and skate (the fish), and polysemous homonyms, or polysemes, which have a ...
The latter two examples would be considered orthographically separate words, though semantically they make up one concept: one is a type of dog and one is a type of rod. In addition to these confusions, wordnets are also idiosyncratic , in that they do not consistently label items.
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 .
A word can be both a hypernym and a hyponym: for example purple is a hyponym of color but itself is a hypernym of the broad spectrum of shades of purple between the range of crimson and violet. The hierarchical structure of semantic fields can be seen in hyponymy. [ 9 ]
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.
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 ...