Homonymy Relation

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A Homonymy Relation is a polysemous relation between two Words that are in a Homophony Relation and a Homography Relation (and of course have different Referents).



  • (Wikipedia, 2019) ⇒ https://en.wikipedia.org/wiki/Homonym Retrieved:2019-1-25.
    • In linguistics, homonyms, broadly defined, are words which sound alike or are spelled alike, but have different meanings. A more restrictive definition sees homonyms as words that are simultaneously homographs (words that share the same spelling, regardless of their pronunciation) and homophones (words that share the same pronunciation, regardless of their spelling)[1] – that is to say they have identical pronunciation and spelling, whilst maintaining different meanings. The relationship between a set of homonyms is called homonymy. Examples of homonyms are 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 shared origin, such as mouth (of a river) and mouth (of an animal). [2] In non-technical contexts, the term "homonym" may be used (somewhat confusingly) to refer to words that are either homographs or homophones.[1] The words row (propel with oars) and row (argument) and row (a linear arrangement of seating) are considered homographs, while the words read (peruse) and reed (waterside plant) would be considered homophones; under this looser definition, both groups of words represent groups of homonyms. The adjective homonymous can additionally be used wherever two items share the same name, independent of how close they are or aren't related in terms of their meaning or etymology.
  • 1.0 1.1 homonym, Random House Unabridged Dictionary at dictionary.com
  • Semantics: a coursebook, p. 123, James R. Hurford and Brendan Heasley, Cambridge University Press, 1983
  • 2009


    • (Jurafsky & Martin, 2009) ⇒ Daniel Jurafsky, and James H. Martin. (2009). “Speech and Language Processing, 2nd edition." Pearson Education.
      • QUOTE: The meaning of a lexeme can very enormously given the context. Consider these two users of the lemma bank ...
      • We represent some of this contextual variation by saying that the lemma bank has two 'senses (footnote: confusingly, the word "lemma" is itself ambiguous; it is also sometimes used to mean these separate senses, rather than the citation form of the word. You should be prepared to see both uses in the literature). A sense (or word sense) is a discrete representation of one aspect of the meaning of a word. Loosely following lexicographic tradition, we represent each sense by placing a superscript on the orthographic form of the lemma as in bank1 and bank2.
      • The sense of a word might not have any particular relation between them; it may be almost coincident that they share an orthographic form. For example, the financial institution and sloping mound sense of bank seem relatively unrelated. In such cases we say that the two senses are homonyms, and the relation between the sense is on of homonymy'
      • When two senses are related semantically, we call the relationship between them polysemy rather than homonymy.
      • While it can be useful to distinguish polysemy from homonymy, there is no hard threshold for how related two senses must be to be considered polysemous. Thus the difference is really one of degree. This face can be make very difficult to decide how many sense a word has.
    (...) We might consider two senses discrete if they have independent truth conditions, different syntactic behavior, and independent sense relations, or if they exhibit antagonistic meaning.
      • One practical technique for determining if two sense are distinct is to conjoin two uses of a word in a single sentence; this kind of conjunction of antagonistic readings is called zeugma.
      • We generally reserve the word homonym for two sense which share both a pronunciation and an orthography. A special case of multiple senses that cause problems for speech recognition and spelling correction is a homophone. Homophones are senses that are linked to lemmas with the same pronunciation but different spellings, such as wood/would or to/two/too. A related problem for speech synthesis are homographs (Chapter 8). Homographs are distinct senses linked to lemmas with the same orthographic form but different pronunciations, such as the homographs of bass.


    • (Shorter OED, 2007) ⇒ Oxford University Press. (2007). “Shorter Oxford English Dictionary, 6th edition.
      • If two or more headwords have the same spelling and part of speech, but each has a different origin and meaning, the headwords are homonyms. They are distinguished by a superscript number after the relevant part of speech. … E.g.
        • cuppernoun1ME.
        • cuppernoun2E20.
        • cupper noun3 variation of CUPPA.




    • (Gale et al., 1992) ⇒ William A. Gale, Kenneth W. Church, and David Yarowsky (1992). “One Sense per Discourse.” In: Proceedings of the DARPA Speech and Natural Language Workshop.
      • It is well-known that there are polysemous words like sentence whose "meaning" or "sense" depends on the context of use. We have recently reported on two new word-sense disambiguation systems, one trained on bilingual material (the Canadian Hansards) and the other trained on monolingual material (Roget's Thesaurus and Grolier's Encyclopedia). As this work was nearing completion, we observed a very strong discourse effect. That is, if a polysemous word such as sentence appears two or more times in a well-written discourse, it is extremely likely that they will all share the same sense. This paper describes an experiment which confirmed this hypothesis and found that the tendency to share sense in the same discourse is extremely strong (98%). This result can be used as an additional source of constraint for improving the performance of the word-sense disambiguation algorithm. In addition, it could also be used to help evaluate disambiguation algorithms that did not make use of the discourse constraint.