Conceptual Abstractness: from Nouns to Verbs

Investigating lexical access, representation and processing involves dealing with conceptual abstractness: abstract concepts are known to be more quickly and easily delivered in human communications than abstract meanings (Binder et al., 2005). Although these aspects have long been left unexplored, they are relevant: abstract terms are widespread in ordinary language, as they contribute to the realisation of various sorts of figurative language (metaphors, metonymies, hyperboles, etc.). Abstractness is therefore an issue for computational linguistics, as well. In this paper we illustrate how to characterise verbs with abstractness information. We provide an experimental evaluation of the presented approach on the largest existing corpus annotated with abstraction scores: our results exhibit good correlation with human ratings, and point out some open issues that will be addressed in future work.In questo lavoro presentiamo il tema dell’astrattezza come una caratteristica diffusa del linguaggio, e un nodo cruciale nell’elaborazione automatica del linguaggio. In particolare illustriamo un metodo per la stima dell’astrattezza che caratterizza i verbi a partire dalla composizione dei punteggi di astrattezza degli argomenti dei verbi utilizzando la risorsa Abs-COVER

Proceedings of the Fifth Italian Conference on Computational Linguistics CLiC-it 2018

On behalf of the Program Committee, a very warm welcome to the Fifth Italian Conference on Computational Linguistics (CLiC-­‐it 2018). This edition of the conference is held in Torino. The conference is locally organised by the University of Torino and hosted into its prestigious main lecture hall “Cavallerizza Reale”. The CLiC-­‐it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after five years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges