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LDA-T3102 Computational Syntax, 5 cr 
Code LDA-T3102  Validity 01.01.2017 -
Name Computational Syntax  Abbreviation Computational S 
Scope5 cr   
TypeAdvanced studies
TypeCourse   
  GradingGeneral scale 
  no
    Can be taken more than onceno
Unit Master’s programme Linguistic Diversity in the Digital Age 

Teachers
Name
Jörg Tiedemann 

Description
Target group 

The course belongs to the MA Programme Linguistic Diversity in the Digital Age

  • study track: language technology
  • modules: Studies in Language Technology (LDA-T3100), Essentials in Language Technology (LDA-TA500), Comprehensive specialization in Language Technology (LDA-TB500)

This is an obligatory course for students of the study track in language technology, and elective for students of modules LDA-TA500 and LDA-TB500 

The course is available to students from other study tracks and degree programmes.


 

 

 

 

 

 
Timing 

Students are advised to take this course in year 1 (semester 2) or in year 2 (semester 3). The course is offered once every year either during the spring term in period III or IV or during the autumn term in period I

 
Learning outcomes 

After successfully completing the course, you will be able to

  • explain formal grammars in relation to the complexity of natural languages
  • implement sequence-labeling models with application to morphosyntactic tagging and syntactic chunking
  • describe and apply essential algorithms for phrase-structure grammars and dependency parsing
  • explain the role of treebanks for grammar induction and parsing.
 
Completion methods 
  • The course comprises lectures and individual exercises.
  • You also complete your own project work, which you document and present in class.
  • Additionally, there may be seminar presentations of relevant literature by students and a final exam.
  • Some sessions require student attendance.
 
Prerequisites 
  • Morphology and syntax or equivalent (BA level)
  • Programming for linguists or equivalent (BA level)
  • Mathematics for linguists or equivalent (BA level)
  • Machine learning for linguists or equivalent (BA level)
 
Recommended optional studies 
  •  Linguistics in the digital age (MA level)
  • Computational Morphology (MA level) 
  • Computational Semantics (MA level)
 
Contents 
  • Sequence models and hierarchical models
  • Formal grammars and natural languages
  • Language models and syntax
  • Morphosyntactic tagging and chunking
  • Parsing with context-free grammars
  • Treebanks and probabilistic grammars
  • Constraint grammar and dependency grammar
  • Dependency parsing
 
Study materials and literature 
  • Jurafsky and Martin: "Speech and Language Processing - An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition" (Prentice Hall}
  • Manning and Schütze: "Foundations of Statistical Natural Language Processing" (MIT Press)
  • Sandra Kübler, Ryan McDonald, and Joakim Nivre: "Dependency Parsing" (Synthesis Lectures on Human Language Technologies, Morgan & Claypool Publishers)
  • Web material and material distributed in the course
 
Activities and teaching methods in support of learning 
  • There are lectures and exercise sessions.
  • Learning is promoted through hands-on assignments, individual projects or group work
  • Exercises, instructions and additional course material are published on a web-based learning platform (Moodle).
 
Assessment practices and criteria 

Grading follows the standard scale 0 – 5.

The following aspects are taken into account in grading

  • Performance in the practical assignments
  • Performance in project work and presentations (if applicable)
  • Performance in the final exam (if applicable)
  • Activity during lectures and exercise sessions.
 


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