Papers by Andrea Bellandi
A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment (2020.lrec-1)
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Sina Ahmadi, John Philip McCrae, Sanni Nimb, Fahad Khan, Monica Monachini, Bolette Pedersen, Thierry Declerck, Tanja Wissik, Andrea Bellandi, Irene Pisani, Thomas Troelsgård, Sussi Olsen, Simon Krek, Veronika Lipp, Tamás Váradi, László Simon, András Gyorffy, Carole Tiberius, Tanneke Schoonheim, Yifat Ben Moshe, Maya Rudich, Raya Abu Ahmad, Dorielle Lonke, Kira Kovalenko, Margit Langemets, Jelena Kallas, Oksana Dereza, Theodorus Fransen, David Cillessen, David Lindemann, Mikel Alonso, Ana Salgado, José Luis Sancho, Rafael-J. Ureña-Ruiz, Jordi Porta Zamorano, Kiril Simov, Petya Osenova, Zara Kancheva, Ivaylo Radev, Ranka Stanković, Andrej Perdih, Dejan Gabrovsek
| Challenge: | a new dataset aims to align monolingual dictionaries with a single sense level for 15 languages . this dataset covers a wide range of languages and resources . |
| Approach: | They propose to manually align monolingual dictionaries with possible semantic relationships . they use 15 languages to create a new baseline for the task of monolingual word sense alignment . |
| Outcome: | The proposed dataset covers 15 languages and covers the more challenging task of linking general-purpose language. |
One Language to rule them all: modelling Morphological Patterns in a Large Scale Italian Lexicon with SWRL (L18-1)
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| Challenge: | Linked data (LD) is a popular way of publishing lexical resources, but technical limitations and potentialities of LD are not understood as they should be. |
| Approach: | They propose to use the Semantic Web Rule Language to encode morphological patterns for a lexicographic publication as linked open data. |
| Outcome: | The proposed language allows the automatic derivation of inflectional variants of entries in the lexicon. |