Fuzzy Lemon: Making Lexical Semantic Relations More Juicy

Fernando Bobillo, Julia Bosque-Gil, Jorge Gracia, Marta Lanau-Coronas


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.
Anthology ID:
2022.ldl-1.6
Volume:
Proceedings of the 8th Workshop on Linked Data in Linguistics within the 13th Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Venue:
LDL
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
45–51
Language:
URL:
https://aclanthology.org/2022.ldl-1.6
DOI:
Bibkey:
Cite (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.
Cite (Informal):
Fuzzy Lemon: Making Lexical Semantic Relations More Juicy (Bobillo et al., LDL 2022)
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PDF:
https://aclanthology.org/2022.ldl-1.6.pdf