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.
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
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.
- 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.
- 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)
- 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.