Computational Lexical Semantics
Lexical semantics is becoming an increasingly important part of Natural Language Processing (NLP), as the field is beginning to address semantics at a large scale. This introductory lecture course will cover key issues in computational lexical semantics. We will start with an introduction to theoretical models of lexical semantics, considering both their adequacy as linguistic models and their place in NLP. We will then examine computational lexical resources and will consider both manual and automatic techniques for their development. The automatic techniques can be used to acquire lexical-semantic information from corpus data. On one extreme, such techniques can be fully supervised (requiring hand-labeled training data). On the other extreme, they can be fully unsupervised (learning lexical information from unlabeled text). In both cases, valuable lexical semantic information can be induced. Towards the end of the course we will discuss the role of lexical semantics in various current NLP applications.
This course will assume basic knowledge in semantics and computational linguistics
Mon & Thu 1:30-3:15
Classroom: MUEN E 432
Areas of Linguistics:
Semantics, Pragmatics and Discourse