@inproceedings{rudnicka-etal-2018-lexical,
title = "Lexical Perspective on {W}ordnet to {W}ordnet Mapping",
author = "Rudnicka, Ewa and
Bond, Francis and
Grabowski, {\L}ukasz and
Piasecki, Maciej and
Piotrowski, Tadeusz",
editor = "Bond, Francis and
Vossen, Piek and
Fellbaum, Christiane",
booktitle = "Proceedings of the 9th Global Wordnet Conference",
month = jan,
year = "2018",
address = "Nanyang Technological University (NTU), Singapore",
publisher = "Global Wordnet Association",
url = "https://aclanthology.org/2018.gwc-1.24",
pages = "209--218",
abstract = "The paper presents a feature-based model of equivalence targeted at (manual) sense linking between Princeton WordNet and plWordNet. The model incorporates insights from lexicographic and translation theories on bilingual equivalence and draws on the results of earlier synset-level mapping of nouns between Princeton WordNet and plWordNet. It takes into account all basic aspects of language such as form, meaning and function and supplements them with (parallel) corpus frequency and translatability. Three types of equivalence are distinguished, namely strong, regular and weak depending on the conformity with the proposed features. The presented solutions are language-neutral and they can be easily applied to language pairs other than Polish and English. Sense-level mapping is a more fine-grained mapping than the existing synset mappings and is thus of great potential to human and machine translation.",
}
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<abstract>The paper presents a feature-based model of equivalence targeted at (manual) sense linking between Princeton WordNet and plWordNet. The model incorporates insights from lexicographic and translation theories on bilingual equivalence and draws on the results of earlier synset-level mapping of nouns between Princeton WordNet and plWordNet. It takes into account all basic aspects of language such as form, meaning and function and supplements them with (parallel) corpus frequency and translatability. Three types of equivalence are distinguished, namely strong, regular and weak depending on the conformity with the proposed features. The presented solutions are language-neutral and they can be easily applied to language pairs other than Polish and English. Sense-level mapping is a more fine-grained mapping than the existing synset mappings and is thus of great potential to human and machine translation.</abstract>
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%0 Conference Proceedings
%T Lexical Perspective on Wordnet to Wordnet Mapping
%A Rudnicka, Ewa
%A Bond, Francis
%A Grabowski, Łukasz
%A Piasecki, Maciej
%A Piotrowski, Tadeusz
%Y Bond, Francis
%Y Vossen, Piek
%Y Fellbaum, Christiane
%S Proceedings of the 9th Global Wordnet Conference
%D 2018
%8 January
%I Global Wordnet Association
%C Nanyang Technological University (NTU), Singapore
%F rudnicka-etal-2018-lexical
%X The paper presents a feature-based model of equivalence targeted at (manual) sense linking between Princeton WordNet and plWordNet. The model incorporates insights from lexicographic and translation theories on bilingual equivalence and draws on the results of earlier synset-level mapping of nouns between Princeton WordNet and plWordNet. It takes into account all basic aspects of language such as form, meaning and function and supplements them with (parallel) corpus frequency and translatability. Three types of equivalence are distinguished, namely strong, regular and weak depending on the conformity with the proposed features. The presented solutions are language-neutral and they can be easily applied to language pairs other than Polish and English. Sense-level mapping is a more fine-grained mapping than the existing synset mappings and is thus of great potential to human and machine translation.
%U https://aclanthology.org/2018.gwc-1.24
%P 209-218
Markdown (Informal)
[Lexical Perspective on Wordnet to Wordnet Mapping](https://aclanthology.org/2018.gwc-1.24) (Rudnicka et al., GWC 2018)
ACL
- Ewa Rudnicka, Francis Bond, Łukasz Grabowski, Maciej Piasecki, and Tadeusz Piotrowski. 2018. Lexical Perspective on Wordnet to Wordnet Mapping. In Proceedings of the 9th Global Wordnet Conference, pages 209–218, Nanyang Technological University (NTU), Singapore. Global Wordnet Association.