Module 02495 (2013)
Syllabus page 2013/2014
06-02495
Natural Language Processing 1
Level 2/I
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus
The Module Description is a strict subset of this Syllabus Page. (The University module description has not yet been checked against the School's.)
Relevant Links
Module web page
Prolog teaching pages
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
- show how Natural Language Processing techniques can be programmed using the Prolog programming language
Learning Outcomes
| On successful completion of this module, the student should be able to: | Assessed by: | |
| 1 | describe major trends and systems in Natural Language Processing | Examination |
| 2 | define: morphology; syntax; semantics; pragmatics; and give appropriate examples to illustrate their definitions | Examination, Continuous Assessment |
| 3 | 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 | Examination, Continuous Assessment |
| 4 | describe simple feature-based semantic systems | Examination, Continuous Assessment |
| 5 | demonstrate a knowledge of at least one method for resolving pronoun referents as an example of semantic interpretation | Examination |
| 6 | describe an application of natural language processing (for instance machine translation) and show the place of syntactic, semantic and pragmatic processing | Examination |
Restrictions, Prerequisites and Corequisites
Restrictions:
None
Prerequisites:
None
Co-requisites:
None
Teaching
Teaching Methods:
2 hrs/week lectures and exercise classes.
Contact Hours:
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".
Recommended Books
| Title | Author(s) | Publisher, Date |
| Speech and language processing: an introduction to Natural Language Processing, Computational Linguistics and Speech Recognition (2nd ed) | Jurafsky D & Martin J H | Prentice Hall, 2008 |
Detailed Syllabus
- Introduction and Overview (1 week)
- Finite State Networks & Transducers (1 week)
- Simple grammars (1 week)
- Basic parsing algorithms (1 week)
- Active chart parsing (1 week)
- Features (1 week)
- Semantics (1 week)
- Discourse Representation Theory (1 week)
- Discourse (1 week)
- Cohesion in Text
- Pronoun Reference Resolution
- Pragmatics (1 week)
- Speech Acts
- Pragmatic Inference
- Applications (1 week)
Last updated: 22 August 2013
Source file: /internal/modules/COMSCI/2013/xml/02495.xml
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus