Module Description - Natural Language Processing 1
The Module Description is a strict subset of the Syllabus Page, which gives more information
| Module Title | Natural Language Processing 1 |
| School | Computer Science |
| Module Code | 06-02495 |
| Descriptor | COMP/06-02495/LI |
| Member of Staff | Mark Lee |
| Level | I |
| Credits | 10 |
| Semester | 2 |
| Pre-requisites | None |
| Co-requisites | 02630 |
| Restrictions | None |
| Contact hours | 23 |
| Delivery | 2 hrs/week lectures and exercise classes. |
| Description | 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. |
| Outcomes | | On successful completion of this module, the student should be able to: | Assessed by: |
| describe major trends and systems in Natural Language
Processing
| Examination |
| define: morphology; syntax; semantics; pragmatics;
and give appropriate examples to illustrate their
definitions
| Coursework and examination |
| 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
| Coursework and examination |
| implement context-free grammars for simple English
| Coursework and examination |
| describe simple feature-based semantic systems typically based on
logic showing the difference between building semantic representations
and interpreting semantic representations
| Coursework and examination |
| demonstrate a knowledge of at least one method for resolving pronoun
referents as an example of semantic interpretation
| Examination |
| show an understanding of the role of pragmatics in understanding
natural language
| Examination |
| describe an application of natural language processing (for instance
machine translation) and show the place of syntactic, semantic and pragmatic
processing
| Examination |
|
| 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". |
| Texts | Jurafsky D & Martin J H, Speech and language processing: an introduction to Natural
Language Processing, Computational Linguistics and Speech Recognition (2nd ed)
, 2008 |