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http://dx.doi.org/10.18419/opus-15000
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DC Element | Wert | Sprache |
---|---|---|
dc.contributor.advisor | Kuhn, Jonas (Prof. Dr.) | - |
dc.contributor.author | Pagel, Janis | - |
dc.date.accessioned | 2024-10-08T08:49:37Z | - |
dc.date.available | 2024-10-08T08:49:37Z | - |
dc.date.issued | 2024 | de |
dc.identifier.other | 190508076X | - |
dc.identifier.uri | http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-150190 | de |
dc.identifier.uri | http://elib.uni-stuttgart.de/handle/11682/15019 | - |
dc.identifier.uri | http://dx.doi.org/10.18419/opus-15000 | - |
dc.description.abstract | This thesis describes experiments on enhancing machine-learning based detection of literary character types in German-language dramatic texts by using coreference information. The thesis makes four major contributions to the research discourse of character type detection and coreference resolution for German dramatic texts: (i) a corpus of annotations of coreference on dramatic texts, called GerDraCor-Coref, (ii) a rule-based system to automatically resolve coreferences on dramatic texts, called DramaCoref, as well as experiments and analyses of results by using DramaCoref on GerDraCor-Coref, (iii) experiments on the automatic detection of three selected character types (title characters, protagonists and schemers) using machine-learning approaches, and (iv) experiments on utilizing the coreference information of (i) and (ii) for improving the performance of character type detection of (iii). | en |
dc.language.iso | en | de |
dc.rights | info:eu-repo/semantics/openAccess | de |
dc.subject.ddc | 004 | de |
dc.subject.ddc | 400 | de |
dc.subject.ddc | 830 | de |
dc.title | Enhancing character type detection using coreference information : experiments on dramatic texts | en |
dc.type | doctoralThesis | de |
ubs.dateAccepted | 2023-11-17 | - |
ubs.fakultaet | Informatik, Elektrotechnik und Informationstechnik | de |
ubs.institut | Institut für Maschinelle Sprachverarbeitung | de |
ubs.publikation.seiten | xxx, 200 | de |
ubs.publikation.typ | Dissertation | de |
ubs.thesis.grantor | Informatik, Elektrotechnik und Informationstechnik | de |
Enthalten in den Sammlungen: | 05 Fakultät Informatik, Elektrotechnik und Informationstechnik |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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thesis.pdf | 5,09 MB | Adobe PDF | Öffnen/Anzeigen |
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