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This paper provides a binary, token-based classification of German particle verbs (PVs) into literal vs. non-literal usage. A random forest improving standard features (e.g., bagof-words; affective ratings) with PV-specific information and abstraction over common nouns significantly outperforms the majority baseline. In addition, PV-specific classification experiments demonstrate the role of shared particle semantics and semantically related base verbs in PV meaning shifts.doi:10.18653/v1/n16-1039 dblp:conf/naacl/KoperW16 fatcat:sqjvfzneibfppepv5qzv7nlm3a