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Classifying Semantic Relations in German Nominal Compounds using a Hybrid Annotation Scheme
Author(s) -
Daniil Sorokin,
Erhard Hinrichs,
Corina Dima
Publication year - 2015
Publication title -
journal of cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.108
H-Index - 4
eISSN - 1976-6939
pISSN - 1598-2327
DOI - 10.17791/jcs.2015.16.3.261
Subject(s) - german , scheme (mathematics) , annotation , computer science , natural language processing , artificial intelligence , information retrieval , mathematics , linguistics , philosophy , mathematical analysis
This paper reports on novel results for the automatic classification of semantic relations that hold between the constituents of nominal compounds in German. It utilizes a hybrid annotation scheme that models semantic relations using a combination of prepositional paraphrases and semantic properties. The machine learning (ML) experiments use the support vector machine (SVM) implementation in Weka for single-label prediction tasks and Weka SVMs in conjunction with the Mulan library for multi-label prediction.

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