Linguistic Data Science follows other areas within science and the humanities by stating that knowledge is justified belief, that belief is based on evidence, and that evidence, finally, can only be determined on the background of theoretical assumptions.
Studies in Linguistics and Linguistic Data Science will publish results that follow these leads.
The dissertation investigates the countability of abstract nouns both empirically and theoretically by combining research from (morpho-)syntax and semantics of noun phrases. Using empirical methods, such as Annotation Mining and corpus analyses, on a sample of polysemous abstract nouns, the thesis draws generalizations relating the countability of abstract nouns to the boundedness of abstract entities and offers a semantic analysis for eventuality denoting nominals.
DownloadThe handbook systematically takes stock of a selection of German simple prepositions – in a two-fold perspective analysing prepositional forms in terms of their senses and inversely covering common senses shared by prepositional forms. The accompanying resource PrepSensNZZ, which is also found under resources, illustrates the annotation process, and supersenses, as well as specific subsenses derived by decision trees and taxonomies, which form part of the annotation system. PrepSensNZZ can also be used independently of SLLDS 2 as a gold standard for preposition sense tagging.
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