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dc.contributor.authorZeller, Tom-
dc.date.accessioned2018-10-31T13:32:28Z-
dc.date.available2018-10-31T13:32:28Z-
dc.date.issued2018de
dc.identifier.other512513902-
dc.identifier.urihttp://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-100982de
dc.identifier.urihttp://elib.uni-stuttgart.de/handle/11682/10098-
dc.identifier.urihttp://dx.doi.org/10.18419/opus-10081-
dc.description.abstractAmbiguity is ever-present in natural language production. A human typically has no difficulties in selecting the right interpretation for an ambiguous expression by using lexical and pragmatic knowledge. While the inclusion of broad semantic knowledge poses a challenge for general disambiguation systems and parsers, its utilization might be a feasible approach for disambiguation in a restricted context. A domain that is very sensitive to ambiguity is the legal domain, especially in the wording of statutory text. Some parsing systems deal with ambiguous input by specifying all possible interpretations without explicitly choosing a solution or by returning multiple parses along with their respective probability. This work serves two purposes: An application is created which allows the input of statutory texts or single text excerpts and which detects included structural ambiguities in the form of prepositional phrase attachments and coordination ambiguities, and semantic ambiguity in the form of scopal ambiguity. Furthermore, the found ambiguities are filtered by including subcategorizational information and by utilizing domain-specific semantic knowledge which is encoded in the form of a legal domain ontology and selectional preferences for common legal expressions. The filtering capability and the effect of including the semantic knowledge are evaluated on the DUBLIN3 Regulation.en
dc.language.isoende
dc.rightsinfo:eu-repo/semantics/openAccessde
dc.subject.ddc004de
dc.titleDetecting ambiguity in statutory textsen
dc.typebachelorThesisde
ubs.fakultaetInformatik, Elektrotechnik und Informationstechnikde
ubs.institutInstitut für Maschinelle Sprachverarbeitungde
ubs.publikation.seiten49de
ubs.publikation.typAbschlussarbeit (Bachelor)de
Enthalten in den Sammlungen:05 Fakultät Informatik, Elektrotechnik und Informationstechnik

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