Skip to main content
Photo: MLT Institutionen för filosofi, lingvistik och vetenskapsteori

Natural language processing

Master’s level
15 credits (ECTS)


This course gives a theoretical view of problems encountered within Natural Language Processing and some solutions.


This course gives a theoretical view of problems encountered within Natural Language Processing and some solutions.

Students will gain practical experience in programming while solving these problems. The programming language used in the course LT2111 (Introduction to programming) will also be used in this course together with standard NLP libraries.

The course is divided into four main topics: one covering basic concepts and three covering subfields of NLP ? words, syntax and semantics/pragmatics.

1. Basic concepts:

  • Basic concepts in NLP.
  • Automata theory and mathematical linguistics.
  • Probability theory and machine learning.
  • Evaluation measurement, correctness, precision, and recall.

2. Words:

  • Corpora and corpus annotation.
  • Finite-state methods for segmentation and morphological analysis.
  • Statistical language modeling with n-gram markov models.

3. Syntax:

  • Part-of-speech tagging and chunking/partial parsing, making use of methods within machine learning or/and finite-state technology.
  • Common formal grammars, such as feature based and probabilistic context-free grammars.
  • Syntactic parsing.

4. Semantics and Pragmatics:

  • Lexical semantics, lexica, Wordnet and FrameNet.
  • Word sense disambiguation with machine learning.
  • Text classification with machine learning.

Prerequisites and selection


For admission to course a Bachelor Degree in some of the following subjects:

computer science, computational linguistics or language technology, linguistics (including at least 30 credits in formal linguistics or programming), adjacent subject, for instance cognitive science, languages, philosophy or mathematics, (provided that the student has got 30 credits either in formal linguistics or programming),
or the equivalent after assessment is required for the admission to course.

Passed knowledge in English equivalent to English 5/English A (upper secondary course level) is mandatory.