Third-Cycle Courses

Faculty of Engineering | Lund University

Details for the Course Syllabus for Course EDAN20F valid from Autumn 2017

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  • In the past 15 years, language technology has considerably matured driven by the massive increase of textual and spoken data and the need to process them automatically. Although there are few systems entirely dedicated to language processing, there are now scores of applications that are to some extent "language-enabled" and embed language processing techniques such as spelling and grammar checkers, information retrieval and extraction, or spoken dialogue systems. This makes the field form a new requirement for the CS engineers.

    The course introduces theories used in language technology. It attempts to cover the whole field from character encoding and statistical language models to semantics and conversational agents, going through syntax and parsing. It focuses on proven techniques as well as significant industrial or laboratory applications.
  • An overview of language technology: disciplines, applications, and examples
    Corpus and word processing: regular expressions, automata, an introduction to Perl, concordances, tokenization, counting words, collocations
    Morphology and part-of-speech tagging: word morphology, transducers, part-of-speech tagging,
    Phrase-structure grammars: constituents, trees, DCG rules, unification.
    Partial parsing: multiword detection, noun group and verb group extraction, information extraction, evaluation
    Syntax: formalisms, constituency and dependency, functions, parsing, statistical parsing, dependency parsing.
    Semantics: formal semantics, lambda-calculus, lexical semantics, predicate--argument structures, frame semantics, semantic parsing.
    Discourse and dialogue: reference and coreference, discourse and rhetoric, discourse relations, parsing discourse relations, dialogue automata, speech acts, multimodality.
Knowledge and Understanding
  • For a passing grade the doctoral student must
  • Understand the field of language technology and major applications using them
    Know the most important techniques, fundamental algorithms, and most common architectures used in applications
    Create and implement language processing algorithms. Write, interpret, evaluate, and improve them during the programming laboratories.
Competences and Skills
  • For a passing grade the doctoral student must
  • Understand and develop annotation schemes, create and process structured documents
    Understand and write regular expressions and use them in languages like Perl or Java
    Use logic and a logic programming language like Prolog
    Understand and use machine--learning algorithms and statistical techniques
    Develop and evaluate algorithms in major fields of language technology: language models, partial parsing, dependency parsing, and semantic parsing using real data.
Judgement and Approach
  • For a passing grade the doctoral student must
  • Show curiosity, creativity, and problem solving aptitudes
    Show an understanding of industrial and research issues in language technology
Types of Instruction
  • Lectures
  • Laboratory exercises
Examination Formats
  • Written exam
  • Failed, pass
Admission Requirements
  • EDAA01 Programming - Second Course
Assumed Prior Knowledge
Selection Criteria
  • Language Processing with Perl and Prolog, Theories, Implementation, and Application. Pierre Nugues, 2014. ISBN 9783642414640.
Further Information
Course code
  • EDAN20F
Administrative Information
  •  -03-22
  • Professor Thomas Johansson

All Published Course Occasions for the Course Syllabus

1 course occasion.

Start Date End Date Published
2021‑08‑30 2021‑10‑31

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