Clustering verbs semantically according to their alternation behaviour

Authors:
Sabine Schulte im Walde
Affiliations:
Universität Stuttgart, Stuttgart, Germany
Venue:
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Year:
2000

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Abstract

Verbs were clustered semantically on the basis of their alternation behaviour, as characterised by their syntactic subcategorisation frames extracted from maximum probability parses of a robust statistical parser, and completed by assigning WordNet classes as selectional preferences to the frame arguments. The clustering was achieved (a) iteratively by measuring the relative entropy between the verbs' probability distributions over the frame types, and (b) by utilising a latent class analysis based on the joint frequencies of verbs and frame types.