@inproceedings{piasecki-etal-2016-plwordnet,
title = "pl{W}ord{N}et in Word Sense Disambiguation task",
author = "Piasecki, Maciej and
K{\k{e}}dzia, Pawe{\l} and
Orli{\'n}ska, Marlena",
editor = "Fellbaum, Christiane and
Vossen, Piek and
Mititelu, Verginica Barbu and
Forascu, Corina",
booktitle = "Proceedings of the 8th Global WordNet Conference (GWC)",
month = "27--30 " # jan,
year = "2016",
address = "Bucharest, Romania",
publisher = "Global Wordnet Association",
url = "https://aclanthology.org/2016.gwc-1.41/",
pages = "282--291",
abstract = "The paper explores the application of plWordNet, a very large wordnet of Polish, in weakly supervised Word Sense Disambiguation (WSD). Because plWordNet provides only partial descriptions by glosses and usage examples, and does not include sense-disambiguated glosses, PageRank-based WSD methods perform slightly worse than for English. However, we show that the use of weights for the relation types and the order in which lexical units have been added for sense re-ranking can significantly improve WSD precision. The evaluation was done on two Polish corpora (KPWr and Sk{\l}adnica) including manual WSD. We discuss the fundamental difference in the construction of both corpora and very different test results."
}
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<abstract>The paper explores the application of plWordNet, a very large wordnet of Polish, in weakly supervised Word Sense Disambiguation (WSD). Because plWordNet provides only partial descriptions by glosses and usage examples, and does not include sense-disambiguated glosses, PageRank-based WSD methods perform slightly worse than for English. However, we show that the use of weights for the relation types and the order in which lexical units have been added for sense re-ranking can significantly improve WSD precision. The evaluation was done on two Polish corpora (KPWr and Składnica) including manual WSD. We discuss the fundamental difference in the construction of both corpora and very different test results.</abstract>
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%0 Conference Proceedings
%T plWordNet in Word Sense Disambiguation task
%A Piasecki, Maciej
%A Kędzia, Paweł
%A Orlińska, Marlena
%Y Fellbaum, Christiane
%Y Vossen, Piek
%Y Mititelu, Verginica Barbu
%Y Forascu, Corina
%S Proceedings of the 8th Global WordNet Conference (GWC)
%D 2016
%8 27–30 jan
%I Global Wordnet Association
%C Bucharest, Romania
%F piasecki-etal-2016-plwordnet
%X The paper explores the application of plWordNet, a very large wordnet of Polish, in weakly supervised Word Sense Disambiguation (WSD). Because plWordNet provides only partial descriptions by glosses and usage examples, and does not include sense-disambiguated glosses, PageRank-based WSD methods perform slightly worse than for English. However, we show that the use of weights for the relation types and the order in which lexical units have been added for sense re-ranking can significantly improve WSD precision. The evaluation was done on two Polish corpora (KPWr and Składnica) including manual WSD. We discuss the fundamental difference in the construction of both corpora and very different test results.
%U https://aclanthology.org/2016.gwc-1.41/
%P 282-291
Markdown (Informal)
[plWordNet in Word Sense Disambiguation task](https://aclanthology.org/2016.gwc-1.41/) (Piasecki et al., GWC 2016)
ACL
- Maciej Piasecki, Paweł Kędzia, and Marlena Orlińska. 2016. plWordNet in Word Sense Disambiguation task. In Proceedings of the 8th Global WordNet Conference (GWC), pages 282–291, Bucharest, Romania. Global Wordnet Association.