2 April 2019, Computational Linguistics Seminar, Sandro Pezzelle

Expressions like "most" or "big" are known to be vague, that is, their interpretation can be borderline and not generally-agreed. Moreover, their use is context-dependent, in a way that an entity can be "big" in one context, but not in another. Interestingly, the meaning of these expressions is shown to be mostly quantitative when they are used to refer to entities (or sets of entities) in real-world contexts; for example, "few" is used by speakers only to refer to a given range of (low) proportions. By exploiting state-of-the-art, cognitively-inspired computational techniques, I tackle the issue of modelling the meaning of vague expressions from their use in grounded contexts, specifically Vision. In the first, longer part of the talk, I will provide an overview of my recent investigations on vague quantifiers ("few", "many", "all", etc.), both at the behavioural and computational level. In the second part, shorter, I will present ongoing research on gradable adjectives ("big", "small", etc.). Any feedback and comment is more than welcome!