Lexical Perspective on Wordnet to Wordnet Mapping

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 synsetlevel mapping of nouns be...

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Bibliographic Details
Main Authors: Rudnicka, Ewa, Bond, Francis, Grabowski, Łukasz, Piasecki, Maciej, Piotrowski, Tadeusz
Other Authors: School of Humanities and Social Sciences
Format: Conference or Workshop Item
Language:English
Published: 2018
Subjects:
Online Access:https://hdl.handle.net/10356/88493
http://hdl.handle.net/10220/44913
http://compling.hss.ntu.edu.sg/events/2018-gwc/pdfs/GWC2018_paper_56.pdf
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Institution: Nanyang Technological University
Language: English
Description
Summary: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 synsetlevel 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.