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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Coreference from the Cross-lingual Perspective
 Novák, Michal ; Žabokrtský, Zdeněk (advisor) ; Stede, Manfred (referee) ; Rosen, Alexandr (referee)
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
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Discovering the structure of natural language sentences by semi-supervised methods
 Rosa, Rudolf ; Žabokrtský, Zdeněk (advisor) ; Tiedemann, Jörg (referee) ; Horák, Aleš (referee)
Discovering the structure of natural language sentences by semi-supervised methods Rudolf Rosa In this thesis, we focus on the problem of automatically syntactically ana- lyzing a language for which there is no syntactically annotated training data. We explore several methods for cross-lingual transfer of syntactic as well as morphological annotation, ultimately based on utilization of bilingual or multi- lingual sentence-aligned corpora and machine translation approaches. We pay particular attention to automatic estimation of the appropriateness of a source language for the analysis of a given target language, devising a novel measure based on the similarity of part-of-speech sequences frequent in the languages. The effectiveness of the presented methods has been confirmed by experiments conducted both by us as well as independently by other respectable researchers. 1
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