Marta Lanau-Coronas


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Fuzzy Lemon: Making Lexical Semantic Relations More Juicy
Fernando Bobillo | Julia Bosque-Gil | Jorge Gracia | Marta Lanau-Coronas
Proceedings of the 8th Workshop on Linked Data in Linguistics within the 13th Language Resources and Evaluation Conference

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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Recent Developments for the Linguistic Linked Open Data Infrastructure
Thierry Declerck | John Philip McCrae | Matthias Hartung | Jorge Gracia | Christian Chiarcos | Elena Montiel-Ponsoda | Philipp Cimiano | Artem Revenko | Roser Saurí | Deirdre Lee | Stefania Racioppa | Jamal Abdul Nasir | Matthias Orlikowsk | Marta Lanau-Coronas | Christian Fäth | Mariano Rico | Mohammad Fazleh Elahi | Maria Khvalchik | Meritxell Gonzalez | Katharine Cooney
Proceedings of the Twelfth Language Resources and Evaluation Conference

In this paper we describe the contributions made by the European H2020 project “Prêt-à-LLOD” (‘Ready-to-use Multilingual Linked Language Data for Knowledge Services across Sectors’) to the further development of the Linguistic Linked Open Data (LLOD) infrastructure. Prêt-à-LLOD aims to develop a new methodology for building data value chains applicable to a wide range of sectors and applications and based around language resources and language technologies that can be integrated by means of semantic technologies. We describe the methods implemented for increasing the number of language data sets in the LLOD. We also present the approach for ensuring interoperability and for porting LLOD data sets and services to other infrastructures, as well as the contribution of the projects to existing standards.

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Graph Exploration and Cross-lingual Word Embeddings for Translation Inference Across Dictionaries
Marta Lanau-Coronas | Jorge Gracia
Proceedings of the 2020 Globalex Workshop on Linked Lexicography

This paper describes the participation of two different approaches in the 3rd Translation Inference Across Dictionaries (TIAD 2020) shared task. The aim of the task is to automatically generate new bilingual dictionaries from existing ones. To that end, we essayed two different types of techniques: based on graph exploration on the one hand and, on the other hand, based on cross-lingual word embeddings. The task evaluation results show that graph exploration is very effective, accomplishing relatively high precision and recall values in comparison with the other participating systems, while cross-lingual embeddings reaches high precision but smaller recall.