Distributional semantics has deeply changed in the last decades. First, predict models stole
the thunder from traditional count ones, and more recently both of them were replaced in …

Ellipsis is a linguistic phenomenon characterized by the omission of one or more sentence
elements. Solving such a linguistic construction is not a trivial issue in natural language …

Most compositional distributional semantic models represent sentence meaning with a
single vector. In this paper, we propose a structured distributional model (SDM) that …

This work addresses some questions about language processing: what does it mean that
natural language sentences are semantically complex? What semantic features can …

We evaluate four count-based and predictive distributional semantic models of Ancient
Greek against AGREE, a composite benchmark of human judgements, to assess their ability …

In the NLP literature, the thematic fit estimation task is defined as the task in which a system
has to predict how likely a candidate argument (eg cop) is to fit a given a verb-specific role …

In this work, we propose a Distributional Semantic resource enriched with linguistic and
lexical information extracted from electronic dictionaries, designed to address the challenge …

Distributional Semantics (DS) models are based on the idea that two words which appear in
similar contexts, ie similar neighborhoods, have similar meanings. This concept was …

This paper addresses the problem of validating human judgments on verb semantic
selection acquired through manual clustering of concordances from a corpus. In addition to …

The purpose of this paper is to evaluate whether distributional techniques applied to lexical
sets, ie the set of fillers of verb argument slots, constitute a useful heuristic to model verb …