Hyponymy

In linguistics, a hyponym is a word or phrase whose semantic range is included within that of another word. For example, "scarlet", "vermilion", "carmine", and "crimson" are all hyponyms of "red" (their hypernym), which is, in turn, a hyponym of "colour".

According to Fromkin and Rodman, [cite book | first = Victoria | last = Fromkin | coauthors = Robert Rodman | title = Introduction to Language | isbn = 0-03-018682-X] hyponyms are a set of related words whose meaning are specific instances of a more general word (so, for example, "red", "white", "blue", etc., are hyponyms of "colour"). Hyponymy is thus the relationship between a general term such as "polygon" and specific instances of it, such as "triangle".

Computer science often terms this relationship an is-a relationship. For example, "Red is a colour" can be used to describe the hyponymic relationship between "red" and "colour".

The term Hypernym denotes a word, usually somewhat vague and broad in meaning, that other more specific words fall under or are fairly encompassed by.

For example, "vehicle" denotes all the things that are separately denoted by the words "train", "chariot", "dogsled", "airplane", and "automobile" and is therefore a hypernym of each of those words. Conversely, the words "train", "chariot" etc. are hyponyms of "vehicle".

Hypernymy is the semantic relation in which one word is the hypernym of another. Hypernymy, the relation words stand in when their extensions stand in the relation of class to subclass, should not be confused with holonymy which is the relation words stand in when the things that they denote stand in the relation of whole to part. A similar warning applies to hyponymy and meronymy.

Automatically finding hypernyms

One of the first suggestions on how to find hypernym/hyponym pairs in a text came from Marti Hearst, who suggested looking at the output of a parser and taking all of the terms linked by constructions such as "X and other Y;" X could be considered a possible hyponym of Y. This method was extended by Snow et al, who developed an automated method of finding possible constructions that could signal such a pair.

Their process works by taking hypernym/hyponym pairs from WordNet and finding many noun-noun pairs from a parsed corpus. They train a classifier to select those pairs of words that have a high probability of being hypernym pairs given the constructions which link the terms in the corpus.

Notes

References

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ee also

* -onym
* synonym
* WordNet (a semantic lexicon for the English language, which puts words in semantic relations to each other, mainly by using the concepts "hypernym" and "hyponym".)
*Sub- and Subcategory
*Meronymy
*Is-a