Terminology extraction using co-occurrence patterns as predictors of semantic relevance

no code implementations • TERM (LREC) 2022 • Rogelio Nazar, David Lindemann

We propose a method for automatic term extraction based on a statistical measure that ranks term candidates according to their semantic relevance to a specialised domain.

Term Extraction

QICHWABASE: A Quechua Language and Knowledge Base for Quechua Communities

no code implementations • 29 Apr 2023 • Elwin Huaman, David Lindemann, Valeria Caruso, Jorge Luis Huaman

Over the last decade, the Web has increasingly become a space of language and knowledge representation.

A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment

1 code implementation • LREC 2020 • Sina Ahmadi, John Philip McCrae, Sanni Nimb, Fahad Khan, Monica Monachini, Bolette Pedersen, Thierry Declerck, Tanja Wissik, Bell, Andrea i, Irene Pisani, Thomas Troelsg{\aa}rd, Sussi Olsen, Simon Krek, Veronika Lipp, Tam{\'a}s V{\'a}radi, L{\'a}szl{\'o} Simon, Andr{\'a}s 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, Jos{\'e} Luis Sancho, Rafael-J. Ure{\~n}a-Ruiz, Jordi Porta Zamorano, Kiril Simov, Petya Osenova, Zara Kancheva, Ivaylo Radev, Ranka Stankovi{\'c}, Andrej Perdih, Dejan Gabrovsek

Aligning senses across resources and languages is a challenging task with beneficial applications in the field of natural language processing and electronic lexicography.