Shalom Lappin
King’s College London
The course considers four central questions
that an adequate theory of semantic representation must
answer. First, how can
the theory express fine grained distinctions of meaning? Second, how is
semantic
entailment expressed in the
theory? Third, how is the pervasive gradience (in
particular the vagueness) of
semantic properties
captured? Finally, how can language learners acquire the class of
representations that
the theory makes
available? I consider these questions with reference to three main approaches
to
formal and computational semantics: model
theory, proof theory, and distributional treatments of meaning
(Vector Space Models). I also explore ways
of developing a probabilistic semantics for natural language.
These questions are addressed in the
context of the guiding concern of computational semantics to develop
robust, wide coverage systems for
representing the semantic properties of natural languages, where these
systems can be effectively learned and
their representations of meanings can be efficiently computed.
Background Reading
Chris Fox and Shalom Lappin
(2005), Foundations of Intensional Semantics, Blackwell, Oxford.
Chris
Fox and Shalom Lappin (2010), Expressiveness
and Complexity in Underspecified Semantics,
Linguistic Analysis 36, Festschrift for Joachim Lambek, pp. 385-417.
Jan
van Eijck and Shalom Lappin
(2012), Probabilistic
Semantics for Natural Language, unpublished
ms, CWI, Amsterdam and King’s College
London.
Representing Meaning and Entailment
Fine Grained Intensional Theories
Property Theory with Curry Typing
Expressive and Computational Power
Probabilistic Semantics