The course gives a survey of theory and computational implementations of representing and reasoning with meaning in natural languages from cognitive, linguistic and computational perspective. We will look at formal theories and computational implementations to model-theoretic semantics (lambda calculus), situated and grounded representations of meaning, semantic grammars (CCG, dependency grammar), distributional representations of lexical meaning and its compositional extensions, approaches to unsupervised machine learning of linguistic representations, and others. An emphasis of the course will be (i) on the nature of representations, (ii) how they satisfy the notion of compositionality, (iii) how they are used in inference or reasoning and (iv) what natural language processing applications are they useful for.
The course webpage can be accessed here.
The course syllabus can be found here.