Exploring Soft-Clustering for German (Particle) Verbs across Frequency Ranges
نویسندگان
چکیده
In this paper we explore the role of verb frequencies and the number of clusters in soft-clustering approaches as a tool for automatic semantic classification. Relying on a large-scale setup including 4,871 base verb types and 3,173 complex verb types, and focusing on synonymy as a taskindependent goal in semantic classification, we demonstrate that low-frequency German verbs are clustered significantly worse than midor high-frequency German verbs, and that German complex verbs are in general more difficult to cluster than German base verbs.
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