@inproceedings{bobillo-etal-2022-fuzzy,
title = "Fuzzy Lemon: Making Lexical Semantic Relations More Juicy",
author = "Bobillo, Fernando and
Bosque-Gil, Julia and
Gracia, Jorge and
Lanau-Coronas, Marta",
editor = "Declerck, Thierry and
McCrae, John P. and
Montiel, Elena and
Chiarcos, Christian and
Ionov, Maxim",
booktitle = "Proceedings of the 8th Workshop on Linked Data in Linguistics within the 13th Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.ldl-1.6/",
pages = "45--51",
abstract = "The OntoLex-Lemon model provides a vocabulary to enrich ontologies with linguistic information that can be exploited by Natural Language Processing applications. The increasing uptake of Lemon illustrates the growing interest in combining linguistic information and Semantic Web technologies. In this paper, we present Fuzzy Lemon, an extension of Lemon that allows to assign an uncertainty degree to lexical semantic relations. Our approach is based on an OWL ontology that defines a hierarchy of data properties encoding different types of uncertainty. We also illustrate the usefulness of Fuzzy Lemon by showing that it can be used to represent the confidence degrees of automatically discovered translations between pairs of bilingual dictionaries from the Apertium family."
}
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<abstract>The OntoLex-Lemon model provides a vocabulary to enrich ontologies with linguistic information that can be exploited by Natural Language Processing applications. The increasing uptake of Lemon illustrates the growing interest in combining linguistic information and Semantic Web technologies. In this paper, we present Fuzzy Lemon, an extension of Lemon that allows to assign an uncertainty degree to lexical semantic relations. Our approach is based on an OWL ontology that defines a hierarchy of data properties encoding different types of uncertainty. We also illustrate the usefulness of Fuzzy Lemon by showing that it can be used to represent the confidence degrees of automatically discovered translations between pairs of bilingual dictionaries from the Apertium family.</abstract>
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%0 Conference Proceedings
%T Fuzzy Lemon: Making Lexical Semantic Relations More Juicy
%A Bobillo, Fernando
%A Bosque-Gil, Julia
%A Gracia, Jorge
%A Lanau-Coronas, Marta
%Y Declerck, Thierry
%Y McCrae, John P.
%Y Montiel, Elena
%Y Chiarcos, Christian
%Y Ionov, Maxim
%S Proceedings of the 8th Workshop on Linked Data in Linguistics within the 13th Language Resources and Evaluation Conference
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F bobillo-etal-2022-fuzzy
%X The OntoLex-Lemon model provides a vocabulary to enrich ontologies with linguistic information that can be exploited by Natural Language Processing applications. The increasing uptake of Lemon illustrates the growing interest in combining linguistic information and Semantic Web technologies. In this paper, we present Fuzzy Lemon, an extension of Lemon that allows to assign an uncertainty degree to lexical semantic relations. Our approach is based on an OWL ontology that defines a hierarchy of data properties encoding different types of uncertainty. We also illustrate the usefulness of Fuzzy Lemon by showing that it can be used to represent the confidence degrees of automatically discovered translations between pairs of bilingual dictionaries from the Apertium family.
%U https://aclanthology.org/2022.ldl-1.6/
%P 45-51
Markdown (Informal)
[Fuzzy Lemon: Making Lexical Semantic Relations More Juicy](https://aclanthology.org/2022.ldl-1.6/) (Bobillo et al., LDL 2022)
ACL
- Fernando Bobillo, Julia Bosque-Gil, Jorge Gracia, and Marta Lanau-Coronas. 2022. Fuzzy Lemon: Making Lexical Semantic Relations More Juicy. In Proceedings of the 8th Workshop on Linked Data in Linguistics within the 13th Language Resources and Evaluation Conference, pages 45–51, Marseille, France. European Language Resources Association.