Natural Language Processing
ZPD Acad. year 2018/2019 Winter semester
Foundations of the natural language processing, language data in corpora, levels of description: phonetics and phonology, morphology, syntax, semantics and pragmatics. Traditional vs. formal grammars: representation of morphological and syntactic structures, meaning representation. context-free grammars and their context-sensitive extensions, DCG (Definite Clause Grammars), CKY algorithm (Cocke-Kasami-Younger), chart-parsing. Problem of ambiguity. Electronic dictionaries: representation of lexical knowledge. Types of the machine readable dictionaries. Semantic representation of sentence meaning. The Compositionality Principle, composition of meaning. Semantic classification: valency frames, predicates, ontologies, transparent intensional logic (TIL) and its application to semantic analysis of sentences. Pragmatics: semantic and pragmatic nature of noun groups, discourse structure, deictic expressions, verbal and non-verbal contexts. Natural language understanding: semantic representation, inference and knowledge representations.
Language of instruction
Subject specific learning outcomes and competences
Students will get acquainted with advanced methods of natural language processing. They will understand the algorithmic description of the main language levels: morphology, syntax, semantics, and pragmatics, as well as the resources of natural language data - corpora. By means of a self-study and a consultation, they will also grasp detailed knowledge of a selected part of the NLP field.
To understand natural language processing and to learn how to apply basic algorithms in this field. To get acquainted with the algorithmic description of the main language levels: morphology, syntax, semantics, and pragmatics, as well as the resources of natural language data - corpora. To conceive basics of knowledge representation, inference, and relations to the artificial intelligence.
Syllabus of lectures
- Advanced methods of text categorization, document similarity
- Morphological analysis, inflective and derivational morphology, trie structure for dictionaries
- Methods of syntactic analysis for language modeling
- Probabilistic context-free analysis, automatic alignment, machine translation
- Lexical semantics, dictionaries vs. encyclopedias, compositionality
- The Semantic Web technologies, ontologies, OWL
Course inclusion in study plans