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A Closer Look at Automatic Selectional Preferences for Latin

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Chapter Summary

This chapter explains the technical details of the selectional preference (SP) model, as well as more general background notions on vector spaces and clustering. It presents the WordNet (WN) synsets relative to some of the nouns used as examples in homo 'man', mundus 'world', and terra 'earth'. In data analysis, one usually deals with tables whose rows correspond to observations and column to variables. The term 'clustering' in data analysis denotes a group of statistical techniques that share the aim of grouping an input set of observations into subsets called clusters. The chapter defines SPs in terms of the probability that certain WN nodes (like ENTITY or OBJECT) are selected by a verb for a given syntactic position (like accusative objects of abeo 'leave'). It analyses the evaluation of the distributional version of the SP algorithm.

Keywords: clustering algorithm; selectional preferences (SP) algorithm; selectional preferences (SPs); WordNet (WN) synsets



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