@inproceedings{loukachevitch-etal-2018-comparing,
title = "Comparing Two Thesaurus Representations for {R}ussian",
author = "Loukachevitch, Natalia and
Lashevich, German and
Dobrov, Boris",
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-1.5",
pages = "34--43",
abstract = "In the paper we presented a new Russian wordnet, RuWordNet, which was semi-automatically obtained by transformation of the existing Russian thesaurus RuThes. At the first step, the basic structure of wordnets was reproduced: synsets{'} hierarchy for each part of speech and the basic set of relations between synsets (hyponym-hypernym, part-whole, antonyms). At the second stage, we added causation, entailment and domain relations between synsets. Also derivation relations were established for single words and the component structure for phrases included in RuWordNet. The described procedure of transformation highlights the specific features of each type of thesaurus representations.",
}
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%0 Conference Proceedings
%T Comparing Two Thesaurus Representations for Russian
%A Loukachevitch, Natalia
%A Lashevich, German
%A Dobrov, Boris
%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 loukachevitch-etal-2018-comparing
%X In the paper we presented a new Russian wordnet, RuWordNet, which was semi-automatically obtained by transformation of the existing Russian thesaurus RuThes. At the first step, the basic structure of wordnets was reproduced: synsets’ hierarchy for each part of speech and the basic set of relations between synsets (hyponym-hypernym, part-whole, antonyms). At the second stage, we added causation, entailment and domain relations between synsets. Also derivation relations were established for single words and the component structure for phrases included in RuWordNet. The described procedure of transformation highlights the specific features of each type of thesaurus representations.
%U https://aclanthology.org/2018.gwc-1.5
%P 34-43
Markdown (Informal)
[Comparing Two Thesaurus Representations for Russian](https://aclanthology.org/2018.gwc-1.5) (Loukachevitch et al., GWC 2018)
ACL
- Natalia Loukachevitch, German Lashevich, and Boris Dobrov. 2018. Comparing Two Thesaurus Representations for Russian. In Proceedings of the 9th Global Wordnet Conference, pages 34–43, Nanyang Technological University (NTU), Singapore. Global Wordnet Association.