400 Sprache, Linguistik
Refine
Document Type
- Part of a Book (2)
- Conference Proceeding (1)
Has Fulltext
- yes (3)
Keywords
- Dativ (3) (remove)
Publicationstate
Reviewstate
- (Verlags)-Lektorat (2)
- Peer-Review (1)
Publisher
- Narr (1)
- Narr Francke Attempto (1)
The relative order of dative and accusative objects in older German is less free than it is today. The reason for this could be that speakers of the direct predecessor of Old High German organized the referents according to the Thematic Hierarchy. If one applies a Case Hierarchy Nom>Acc>Dat to this, the order Nom - Dat - Acc falls out. It becomes apparent that the status of the Thematic Hierarchy is not a factor governing underlying word order, but a factor inducing scrambling. Arguments from binding theory, whose validity is discussed, indicate that the underlying order is ‘accusative before dative’
Die sprachlichen Auffälligkeiten, die in Gedichten zu beobachten sind, haben immer wieder Anlass zu verschiedenen Versionen der Abweichungstheorie gegeben, derzufolge die in Gedichten verwendete Sprache von nicht-lyrischer Sprache abweicht. Expressionistische Lyrik ist insbesondere für ihre argumentstrukturellen Innovationen bekannt. Auf der Basis eines Korpus expressionistischer Gedichte wird eine Übersicht über diese Auffälligkeiten gegeben, die die Grundlage für weitere Studien darstellen soll, in denen zu zeigen sein wird, inwieweit unter bestimmten grammatiktheoretischen Annahmen die Abweichungstheorie zurückgewiesen werden kann.
We investigate whether non-configurational languages, which display more word order variation than configurational ones, require more training data for a phenomenon to be parsed successfully. We perform a tightly controlled study comparing the dative alternation for English (a configurational language), German, and Russian (both non-configurational). More specifically, we compare the performance of a dependency parser when only canonical word order is present with its performance on data sets when all word orders are present. Our results show that for all languages, canonical data not only is easier to parse, but there exists no direct correspondence between the size of training sets containing free(er) word order variation and performance.