The notion of salience in the discourse analysis models how the activation of referred objects evolves in the flow of text. The salience algorithm was already defined and tested briefly in an earlier research, we present a reproduction of its results in a larger scale using data from the Prague Discourse Treebank 1.0. The results are then collected into an accessible shape and analyzed both in their visual and quantitative form in the context of the two main resources of the salience - coreference relations and topic-focus articulation. Finally, attempts are made with using the salience information in the machine learning NLP tasks of document clustering and topic modeling. Powered by TCPDF (www.tcpdf.org)

Coreference from the Cross-lingual Perspective Michal Nov'ak The subject of this thesis is to study properties of coreference using cross- lingual approaches. The work is motivated by the research on coreference-related linguistic typology. Another motivation is to explore whether differences in the ways how languages express coreference can be exploited to build better models for coreference resolution. We design two cross-lingual methods: the bilingually informed coreference resolution and the coreference projection. The results of our experiments with the methods carried out on Czech-English data suggest that with respect to coreference English is more informative for Czech than vice versa. Furthermore, the bilingually informed resolution applied on parallel texts has managed to outperform the monolingual resolver on both languages. In the experiments, we employ the monolingual coreference resolver and an improved method for alignment of coreferential expressions, both of which we also designed within the thesis. 1

The notion of salience in the discourse analysis models how the activation of referred objects evolves in the flow of text. The salience algorithm was already defined and tested briefly in an earlier research, we present a reproduction of its results in a larger scale using data from the Prague Dependency Treebank 3.0. The results are then collected into an accessible shape and analyzed both in their visual and quantitative form in the context of the two main resources of the salience - coreference relations and topic-focus articulation. Furthermore, a possibility of modeling the salience degree by a machine learning algorithm (decision trees and random forest) is examined. Finally, attempts are made with using the salience information in the machine learning NLP task of document clustering visualization. Powered by TCPDF (www.tcpdf.org)

The thesis deals with the relationship between anaforization of name syntagma and determination , which can be seen as an exponent of the anaforization process. The purpose of this work is to evaluate what role had the individual determinants in old French in comparison to their role in contemporary French. The thesis is based on the specialized literature and analysis of anaforical name syntagmas in the text Aucassin et Nicolette. The work is divided into two main parts. The first theoretical part is focused on defining the basic concepts using specialized literature on which the analysis is based and the second part is mainly the analysis itself of nominal syntagmas in the text Aucassin et Nicolette.

This diploma thesis deals with the analysis of the comic book´s texts. The objective of this thesis is the analysis of relationships in this kind of texts, with a special focus on its illustrational constituent part and on the description of several types of anaphora. As a model to the elaboration of this thesis were a few of comic books Astérix, published in French language. The thesis is divided into a theoretical and an analytical part. The theoretical part contains three different chapters. First of them deals with the description of comic books as an individual art, the second one describe the comic books Astérix and the third one is dedicated to the linguistic terms, which are closely connected to this subject. All referential relationships between the referential parts of some of comic books Astérix are demonstrated in the analytical part.

The goal of information extraction is to retrieve relational data from texts written in natural human language. Applications of such obtained information is wide - from text summarization, through ontology creation up to answering questions by QA systems. This work describes design and implementation of a system working in computer cluster which transforms a dump of Wikipedia articles to a set of extracted information that is stored in distributed RDF database with a possibility to query it using created user interface.

The aim of this thesis is to find out how co-referential relationships in Czech texts are developed in terms of the information and constituent structures. The data was processed using the following methods. Firstly I examined the available literature on information and constituent structures with special attention being paid to the formation of coreferential relations. This information was then compared to my own research. With regards to disparities between the approaches, it was necessary to introduce some basic terms that are used within my thesis (Chapter 2). Thereafter, I was able to introduce current approaches to the thesis, including the methodological basis of my work, which is represented by the foreign Centering Theory, because unlike other Czech approaches this theory includes predictions on the frequency of different ways of co-referential relationship development (Chapter 3). Secondly, the knowledge gained from literature was applied to two different types of data: corpus material of Prague Dependency Treebank and material obtained through a questionnaire survey (Chapter 4). The most appropriate methods of developing co-referential chains in the Czech text were determined by challenging the prediction model with the obtained data set. Using this method we gained information about...