Natural Language Engineering (G5119)

15 credits, Level 5

Autumn teaching

In this module, you are introduced to techniques and concepts involved in the analysing of text by machine - with particular emphases on various practical applications that this technology drives.

You study core, generic text processing models, such as:

  • segmentation
  • stemming
  • part-of-speech tagging
  • named entity recognition
  • phrasal chunking
  • dependency parsing.

You also cover related problems and application areas, such as:

  • document classification
  • information retrieval
  • information extraction.

As part of this, you make extensive use of the Natural Language Toolkit, which is a collection of natural language processing tools written in the Python programming language.


50%: Lecture
50%: Practical (Laboratory)


50%: Coursework (Report)
50%: Examination (Unseen examination)

Contact hours and workload

This module is 150 hours of work. This breaks down into 44 hours of contact time and 106 hours of independent study.

This module is running in the academic year 2019/20. We also plan to offer it in future academic years. It may become unavailable due to staff availability, student demand or updates to our curriculum. We’ll make sure to let our applicants know of such changes to modules at the earliest opportunity.