FI:PA153 NL Processing - Course Information
PA153 Natural Language Processing
Faculty of InformaticsAutumn 2008
- Extent and Intensity
- 2/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).
- Teacher(s)
- prof. PhDr. Karel Pala, CSc. (lecturer)
- Guaranteed by
- prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: prof. PhDr. Karel Pala, CSc. - Timetable
- Thu 14:00–15:50 B411
- Prerequisites
- Logical programming I Logical analysis of natural language I and II
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 22 fields of study the course is directly associated with, display
- Course objectives
- The course offers a deeper knowledge about the natural language processing and computational linguistics.
The students will learn about the particular levels of linguistic analysis - morphology, syntax, semantics and pragmatics.
They will be able to use language data - corpora, types of corpora, corpus tools, perform tagging corpus texts, disambiguation with rule based and statistical systems.
They will be acquainted with representation of the morphological stuctures, notation and algorithms for morphological analysis.
The students will be able to work with the representations of syntactic structures - formal grammars and their types. They will learn about context-free, functional and definite-clause grammars and related parsing algorithms.
The data structures such as valency frames and their types will be explained as well.
They will learn about lexical semantics - meanings of words and collocations, machine readable dictionaries, lexical databases (WordNet, EuroWordNet, thesauri).
Semantic analysis of sentence, principles of logical semantic and Normal Translation Algorithm will be presented.
Pragmatics and discourse analysis and its segmentation, anaphora and (co-)reference will be explained.
The students obtain basic knowledge about dialogue systems, inference systems and knowledge representation for NLP systems.
They will be able to understand the principles of the communication agents and main evaluation techniques. - Syllabus
- Natural language processing and computational linguistics.
- Natural language and understanding.
- Levels of linguistic analysis - morphology, syntax, semantics.
- Language data - corpora. Types of corpora. Corpus tools. Tagging corpus texts. Disambiguation, rule based and statistical systems.
- Representation of the morphological stuctures, notation, morphological algorithms.
- Representation of syntactic structures - formal grammars and their types. Context-free and definite-clause grammars. Parsing algorithms. Valency frames and their types.
- Semantic representation. Lexical meanings (words and collocations), machine readable dictionaries, lexical databases (WordNet, EuroWordNet, thesauri).
- Semantic analysis of sentence meaning, Normal Translation Algorithm.
- Pragmatics.
- Discourse analysis and its segmentation. Anaphora and (co-)reference.
- Inference and knowledge representation for NL systems.
- Dialogue systems.
- Communication agents.
- Evaluation techniques
- Literature
- Assessment methods
- oral exam written test
- Language of instruction
- Czech
- Further Comments
- The course is taught annually.
- Enrolment Statistics (Autumn 2008, recent)
- Permalink: https://is.muni.cz/course/fi/autumn2008/PA153