Lexical Perspective on Wordnet to Wordnet Mapping
Date of Issue2018
The 9th Global WordNet Conference (GWC 2018)
School of Humanities and Social Sciences
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.
© 2018 The author(s). This is the author created version of a work that has been peer reviewed and accepted for publication by The 9th Global WordNet Conference (GWC 2018). It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The full-text is available at: [http://compling.hss.ntu.edu.sg/events/2018-gwc/pdfs/GWC2018_paper_56.pdf].