Year: 2021
Type: article
Abstract: Over the course of the last few years, lexicography has witnessed the burgeoning of increasingly reliable automatic approaches supporting the creation of lexicographic resources such as dictionaries, lexical knowledge bases and annotated datasets. In fact, recent achievements in the field of Natural Language Processing and particularly in Word Sense Disambiguation have widely demonstrated their effectiveness not only for the creation of lexicographic resources, but also for enabling a deeper analysis of lexical-semantic data both within and across languages. Nevertheless, we argue that the potential derived from the connections between the two fields is far from exhausted. In this work, we address a serious limitation affecting both lexicography and Word Sense Disambiguation, i.e. the lack of high-quality sense-annotated data and describe our efforts aimed at constructing a novel entirely manually annotated parallel dataset in 10 European languages. For the purposes of the present paper, we concentrate on the annotation of morpho-syntactic features. Finally, unlike many of the currently available sense-annotated datasets, we will annotate semantically by using senses derived from high-quality lexicographic repositories.
Authors: Martelli, Federico, Navigli, Roberto, Krek, Simon, Kallas, Jelena, Gantar, Polona, Koeva, Svetla, Nimb, Sanni, Pedersen, Bolette Sandford, Olsen, Sussi, Langemets, Margit, Koppel, Kristina, Üksik, Tiiu, Dobrovoljc, Kaja, Rafael-J. Ureña-Ruiz, José-Luis Sancho-Sánchez, Lipp, Veronika, Váradi, Tamás, Győrffy, András, László, Simon, Quochi, Valeria, Monachini, Monica, Frontini, Francesca, Tiberius, Carole, Tempelaars, Rob, Costa, Rute, Salgado, Ana, Čibej, Jaka, Munda, Tina
Institutions: Sapienza University of Rome, Jožef Stefan Institute, Jožef Stefan International Postgraduate School, Institute of the Estonian Language, University of Ljubljana, Bulgarian Academy of Sciences, Institute for Bulgarian Language, Det Danske Sprog- og Litteraturselskab (Denmark), University of Copenhagen, Real Academia Española, ELTE Research Centre for Linguistics, Institute for Computational Linguistics “A. Zampolli”, Instituut voor de Nederlandse Taal, Centro de Linguística, Universidade Nova de Lisboa
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4287029782