Computational Semantics (Master S2 Class)

Basic information

Description

This course presents the field of computational semantics. One part of the course focuses on how lambda-calculus can be used to compositionally translate syntactic structure into first-order-logic semantic representations. Another part focuses on common tasks related to computational semantics, such as word sense disambiguation, topic modeling, named entity recognition, or anaphora resolution. The course ends with a brief overview of the different types of semantic representations used in computational linguistics.

Prerequisites

Programming skills in Python. Basic knowledge in set theory. Basic knowledge in graph theory. Basic understanding of context-free grammars.

Learning outcomes

On successful completion of this course, students should:

  • master the basics of compositional semantics,
  • understand how to tackle some of the most common tasks in computational semantics,
  • have basic knowledge of the range of semantic frameworks (both logic-based and not) available in natural language processing.