In this course we will look at a number of themes which relate logic based formal semantics and computational semantics. In the first lecture we will start by drawing a parallel between the kind of models used in model theoretic semantics and databases and show how this can be exploited for natural language interfaces to databases. In the second lecture we will look at the nature of ambiguity in natural language, the kind of problems this creates for computational semantics and proposals that have been made to give underspecified meaning representations that cover several meanings in a single computational representation. In the third lecture we will consider the fact that semantics provides us with a tool to explain inferences that we draw when we are presented with information in natural language. We will consider how natural language semantics can be related to theorem provers and discuss the extent to which the inferences we need to account for in natural language are logical inferences. In the fourth lecture we will discuss how logical semantics is related to dynamic linguistic processing in real time and how this can give us a logic based view of dialogue management, that is, determining what a implemented dialogue system should say at a given point in a dialogue. Finally, in the fifth lecture we will look towards a future for computational semantics where machines learn new meanings as they interact with users, using their previous linguistic experience as a resource. We will suggest that a certain kind of type theory could play an important role in this development.
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