Module 06-02495 (2018)

Natural Language Processing 1

Level 2/I

Outline

The module presents an overview of Natural Language Processing and its applications, followed by introductions to morphology, syntax and semantics. These topics are used to introduce some linguistic theory and appropriate algorithms for their computational implementation. Examples are mostly given using Prolog.

Aims

The aims of this module are to:

introduce Natural Language Processing as one of the components of Artificial Intelligence, both from engineering and cognitive viewpoints

provide foundations for the programming of Natural Language Processing techniques.

Learning Outcomes

On successful completion of this module, the student should be able to:

Describe major concepts, trends, approaches/systems, and difficulties in Natural Language Processing and the study of language generally.

Discuss and illustrate the potential distinctions between morphology, syntax, semantics and pragmatics

Demonstrate knowledge of at least one method for a task such as pronoun reference resolution, coreference resolution, or named-entity recognition as an example of a specific, core task in interpretation.

Describe an application of natural language processing (for instance machine translation or document summarization) and show the place of syntactic, semantic and pragmatic processing.

Restrictions

None

Teaching methods

2 hrs/week lectures and exercise classes.

Contact Hours:
23

Assessment

Sessional: 1.5 hr examination (80%), continuous assessment (20%).

Supplementary (where allowed): By examination only.

The nature and timing of the continuous assessment will be specified on the module web page -- see under "Relevant Links".