Paper: Combining EM Training and the MDL Principle for an Automatic Verb Classification Incorporating Selectional Preferences

ACL ID P08-1057
Title Combining EM Training and the MDL Principle for an Automatic Verb Classification Incorporating Selectional Preferences
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

This paper presents an innovative, complex approach to semantic verb classification that relies on selectional preferences as verb prop- erties. The probabilistic verb class model un- derlying the semantic classes is trained by a combination of the EM algorithm and the MDL principle, providing soft clusters with two dimensions (verb senses and subcategori- sation frames with selectional preferences) as a result. A language-model-based evaluation shows that after 10 training iterations the verb class model results are above the baseline re- sults.