no code implementations • NAACL 2018 • Maja Buljan, Sebastian Pad{\'o}, Jan {\v{S}}najder
LexSub is a more natural task, enables us to evaluate meaning composition at the level of individual words, and provides a common ground to compare CDSMs with dedicated LexSub models.
no code implementations • COLING 2018 • Carlos Ramisch, Silvio Ricardo Cordeiro, Agata Savary, Veronika Vincze, Verginica Barbu Mititelu, Archna Bhatia, Maja Buljan, C, Marie ito, Polona Gantar, Voula Giouli, Tunga G{\"u}ng{\"o}r, Abdelati Hawwari, Uxoa I{\~n}urrieta, Jolanta Kovalevskait{\.e}, Simon Krek, Timm Lichte, Chaya Liebeskind, Johanna Monti, Carla Parra Escart{\'\i}n, Behrang Qasemizadeh, Renata Ramisch, Nathan Schneider, Ivelina Stoyanova, Ashwini Vaidya, Abigail Walsh
Corpora were created for 20 languages, which are also briefly discussed.
no code implementations • WS 2017 • Maja Buljan, Jan {\v{S}}najder
As multiword expressions (MWEs) exhibit a range of idiosyncrasies, their automatic detection warrants the use of many different features.
no code implementations • SEMEVAL 2019 • Niko Pali{\'c}, Juraj Vladika, Dominik {\v{C}}ubeli{\'c}, Ivan Lovren{\v{c}}i{\'c}, Maja Buljan, Jan {\v{S}}najder
In this paper, we demonstrate the system built to solve the SemEval-2019 task 4: Hyperpartisan News Detection (Kiesel et al., 2019), the task of automatically determining whether an article is heavily biased towards one side of the political spectrum.
no code implementations • WS 2019 • Antonio {\v{S}}ajatovi{\'c}, Maja Buljan, Jan {\v{S}}najder, Bojana Dalbelo Ba{\v{s}}i{\'c}
Automatic Term Extraction (ATE) extracts terminology from domain-specific corpora.
no code implementations • LREC 2020 • Maja Buljan, Joakim Nivre, Stephan Oepen, Lilja {\O}vrelid
We discuss methodological choices in contrastive and diagnostic evaluation in meaning representation parsing, i. e. mapping from natural language utterances to graph-based encodings of its semantic structure.