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Detecting semantic relations in texts and their integration with external data resources
Kríž, Vincent ; Vidová Hladká, Barbora (advisor)
We present a strategy to automate the extraction of semantic relations from texts. Both machine learning and rule-based techniques are investigated and the impact of different linguistic knowledge is analyzed for the various approaches. To implement the extraction system RExtractor, several natural language processing tools have been improved: from sentence splitting and tokenization modules to dependency syntax parsers. Furthermore, we created the Czech Legal Text Treebank with several layers of linguistic annotation, which is used to train and test each stage of the proposed system. As a result of the performed work, new Semantic Web resources and tools are available for automatic processing of texts.
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Detecting semantic relations in texts and their integration with external data resources
Kríž, Vincent ; Vidová Hladká, Barbora (advisor) ; Harašta, Jakub (referee) ; Pecina, Pavel (referee)
We present a strategy to automate the extraction of semantic relations from texts. Both machine learning and rule-based techniques are investigated and the impact of different linguistic knowledge is analyzed for the various approaches. To implement the extraction system RExtractor, several natural language processing tools have been improved: from sentence splitting and tokenization modules to dependency syntax parsers. Furthermore, we created the Czech Legal Text Treebank with several layers of linguistic annotation, which is used to train and test each stage of the proposed system. As a result of the performed work, new Semantic Web resources and tools are available for automatic processing of texts.
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Detecting semantic relations in texts and their integration with external data resources
Kríž, Vincent ; Vidová Hladká, Barbora (advisor)
We present a strategy to automate the extraction of semantic relations from texts. Both machine learning and rule-based techniques are investigated and the impact of different linguistic knowledge is analyzed for the various approaches. To implement the extraction system RExtractor, several natural language processing tools have been improved: from sentence splitting and tokenization modules to dependency syntax parsers. Furthermore, we created the Czech Legal Text Treebank with several layers of linguistic annotation, which is used to train and test each stage of the proposed system. As a result of the performed work, new Semantic Web resources and tools are available for automatic processing of texts.
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Verbal Valency in a Cross-Linguistic Perspective
Šindlerová, Jana ; Lopatková, Markéta (advisor) ; Petkevič, Vladimír (referee) ; Malá, Markéta (referee)
Verbal Valency in a Cross-Linguistic Perspective Jana Šindlerová Abstract In the thesis, we look upon differences in argument structure of verbs considering the Czech language and the English language. In the first part, we describe the process of building the CzEngVallex lexicon. In the second part, based on the aligned data of the Prague Czech-English Dependency Treebank, we compare the valencies of verbal translation equivalents and comment of their differences. We classify the differences according to their underlying causes. The causes can be based in the linguistic structure of the languages, they can include translatological reasons, or they can be grounded in the character of the descriptive linguistic theory used.
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