Words and phrases associate with each other to form a semantic network. Characterizing such associations is a first step toward understanding natural languages for machines. Psychologists and linguists have used concepts such as typicality and basic level conceptualization to characterize such associations. However, how to quantify such concepts is an open problem. Recently, much work has focus...

NYU Stephen Schiffer claims (in the present collection) that vagueness is essentially a psychological phenomenon. According to him, vagueness should not be explicated in terms of absent truth values or incurable ignorance—that is, as a semantic or an epistemic phenomenon—but rather in terms of a peculiar new type of propositional attitude. Schiffer introduces the notion of a vagueness-related p...

We study the design of an information retrieval (IR) system that assists customer service agents while they interact with end-users. The type of IR needed is difficult because of the large lexical gap between problems as described by customers, and solutions. We describe an approach that bridges this lexical gap by learning semantic relatedness using tensor representations. Queries that are sho...

In this paper, we put forward a semantic analysis of constructions prepositional phrases introduced by the preposition para with locative meaning combined verbs ser, estar and ficar. proposal, characterise these regarding properties individual-level/ stage-level, modal reading, vagueness location, as well restrictions imposed on subject related to some lexical features, in particular [movable] ...

How can natural language be ‘understood’ by computers? Or, more specifically, how can the semantics of a natural language statement be modeled by means of logic in order to facilitate formal reasoning? This perennial problem has many, partly intertwined facets; one of them being the pervasiveness of vagueness in all natural languages. Originally discarded by Frege as a ‘defect’ of ordinary lang...

the system we present in this contribution is a sub-part of an extensive natural language processing architecture. It is devoted to a particular phenomenon in natural language : the polysemy of words, which produces effects such as vagueness and fuzziness and impedes the normal automatized processing of sentences. We try to show in this paper how our architecture, currently running on a network...

This system generates plausible threedimensional visualizations of basic English descriptions of a zoo environment (mainly animals and plants) by means of a Monte Carlo simulation. It combines a semantic network and an inheritance-based knowledge base as representations for explicit and implicit spatial information, respectively. Its linguistically motivated aspects address underspecification, ...