HIOK0005FU Language Processing 2

Volume 2025/2026
Education

IT and Cognition

Content

Have you ever wondered how to build a system that can process text automatically, for example translate between languages, reveal syntactic structure, or extract semantic information?  

In this class we further develop the knowledge of Natural Language Processing (NLP) methods  you have acquired in the Language Processing 1 unit by exploring more complex NLP algorithms and models. We focus on the application of these algorithms and models to key aspects of automatic text analysis, such as part of speech tagging, named entity recognition and syntactic parsing. We also work on a more specific application such as author verification or hate speech profiling. 

The format of the class consists of lectures, student presentations, hands-on exercises and project work.


The main focus will be on the practical implementation of methods for syntactic parsing. The format of the class consists of lectures (including guest lectures), student presentations, and project work.

Learning Outcome

Academic objectives

See the curriculum:

MA-level 
2019 curriculum

See all the curriculums.

 

 

  • Category
  • Hours
  • Class Instruction
  • 28
  • Preparation
  • 105
  • Exam Preparation
  • 73
  • Total
  • 206
Continuous feedback during the course of the semester
Credit
7,5 ECTS
Type of assessment
Written assignment
Type of assessment details
Take-home assignment, set subject
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Re-exam

Take-home assignment, set subject