COMPGI19 - Statistical Natural Language Processing

This database contains the 2016-17 versions of syllabuses. Syllabuses from the 2015-16 session are available here.

Note: Whilst every effort is made to keep the syllabus and assessment records correct, the precise details must be checked with the lecturer(s).

CodeCOMPGI19 (also taught as COMPM083)
Taught BySebastian Riedel (100%)
AimsThe course introduced the basics of statistical natural language processing (NLP) including both linguistics concepts such as morphology and syntax and machine learning techniques relevant for NLP.
Learning Outcomes

Students successfully completing the module should understand:

  • relevant linguistic concepts
  • relevant ML techniques, in particular structured prediction
  • what makes NLP challenging (and exciting)
  • how to write programs that process language
  • how to rigorously formulate NLP tasks as learning and inference tasks, and address the computational challenges involved.


NLP is domain-centred fields, as opposed to technique centred fields such as ML, and as such there is no "theory of NLP" which