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        <title>Semantic Analysis of Verb-Noun Derivation in Princeton WordNet</title>
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        <namePart type="given">Verginica</namePart>
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    <abstract>We present here the results of a morphosemantic analysis of the verb-noun pairs in the Princeton WordNet as reflected in the standoff file containing pairs annotated with a set of 14 semantic relations. We have automatically distinguished between zero-derivation and affixal derivation in the data and identified the affixes and manually checked the results. The data show that for each semantic relation an affix prevails in creating new words, although we cannot talk about their specificity with respect to such a relation. Moreover, certain pairs of verb-noun semantic primes are better represented for each semantic relation, and some semantic clusters (in the form of WordNet subtrees) take shape as a result. We thus employ a large-scale data-driven linguistically motivated analysis afforded by the rich derivational and morphosemantic description in WordNet to the end of capturing finer regularities in the process of derivation as represented in the semantic properties of the words involved and as reflected in the structure of the lexicon.</abstract>
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%0 Conference Proceedings
%T Semantic Analysis of Verb-Noun Derivation in Princeton WordNet
%A Mititelu, Verginica
%A Leseva, Svetlozara
%A Stoyanova, Ivelina
%Y Vossen, Piek
%Y Fellbaum, Christiane
%S Proceedings of the 11th Global Wordnet Conference
%D 2021
%8 January
%I Global Wordnet Association
%C University of South Africa (UNISA)
%F mititelu-etal-2021-semantic
%X We present here the results of a morphosemantic analysis of the verb-noun pairs in the Princeton WordNet as reflected in the standoff file containing pairs annotated with a set of 14 semantic relations. We have automatically distinguished between zero-derivation and affixal derivation in the data and identified the affixes and manually checked the results. The data show that for each semantic relation an affix prevails in creating new words, although we cannot talk about their specificity with respect to such a relation. Moreover, certain pairs of verb-noun semantic primes are better represented for each semantic relation, and some semantic clusters (in the form of WordNet subtrees) take shape as a result. We thus employ a large-scale data-driven linguistically motivated analysis afforded by the rich derivational and morphosemantic description in WordNet to the end of capturing finer regularities in the process of derivation as represented in the semantic properties of the words involved and as reflected in the structure of the lexicon.
%U https://aclanthology.org/2021.gwc-1.13
%P 108-117

Markdown (Informal)

[Semantic Analysis of Verb-Noun Derivation in Princeton WordNet](https://aclanthology.org/2021.gwc-1.13) (Mititelu et al., GWC 2021)

• Semantic Analysis of Verb-Noun Derivation in Princeton WordNet (Mititelu et al., GWC 2021)

ACL

• Verginica Mititelu, Svetlozara Leseva, and Ivelina Stoyanova. 2021. Semantic Analysis of Verb-Noun Derivation in Princeton WordNet. In Proceedings of the 11th Global Wordnet Conference, pages 108–117, University of South Africa (UNISA). Global Wordnet Association.