Module 06-02495 (2010)
Natural Language Processing 1
|John Barnden||Semester 2||10 credits|
Co-ordinator: John Barnden
Reviewer: Peter Hancox
The Module Description is a strict subset of this Syllabus Page.
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
- show how Natural Language Processing techniques can be programmed using the Prolog programming language
On successful completion of this module, the student should be able to:
- describe major trends and systems in Natural Language Processing
- define: morphology; syntax; semantics; pragmatics; and give appropriate examples to illustrate their definitions
- describe several standard methods of applying morphological and syntactic knowledge in Natural Language Processing systems, for instance: finite-state methods; probabilistic methods; context-free grammars and parsers, including the Active Chart Parsers; unification grammars and parsing
- implement context-free grammars implemented by Prolog's Definite Clause Grammar
- describe simple feature-based semantic systems typically based on logic showing the difference between building semantic representations and interpreting semantic representations
- demonstrate a knowledge of two or more methods for resolving pronoun referents as an example of semantic interpretation
- show an understanding of the role of pragmatics in understanding natural language
- describe an application of natural language processing (for instance machine translation) and show the place of syntactic, semantic and pragmatic processing
- 06-02630 - Software Workshop Prolog
2 hrs/week lectures and exercise classes.
- Sessional: 1.5 hr examination (50%), continuous assessment (50%).
- Supplementary: By examination only.
- (This is copied form previous years. It is a rough guide only, as the coverage of topics this year will be significantly different.)
- Introduction - What is language and Natural Language Processing?
- What does it mean to know a language?
- What do we know when we know a natural language?
- What is meant by Natural Language Understanding
- Word-level descriptions (1.5 week)
- Morphology and morphological processing
- The lexicon
- Syntax and Syntactic Processors (4 weeks)
- Lexical and syntactic categories
- Introduction to the terminology of syntax and context-free grammars
- Part-of-Speech Tagging
- From Finite State Automata to Context-Free Grammars
- Definite Clause Grammar and the Very Simple Parser
- Active Chart Parsers
- Unification-based grammars and parsing
- Semantics and pragmatics (3 weeks)
- Introduction to semantics and semantic processing
- Building semantic structures
- Building more complex structures and semantic interpretation
- Discourse structure and reasoning
- Application of Natural Language Processing (1 week)
- Machine translation