Towards an Inventory of English Verb Argument Constructions

This paper outlines and pilots our approach towards developing an inventory of verb-argument constructions based upon English form, function, and usage. We search a tagged and dependency-parsed BNC (a 100-million word corpus of English) for Verb-Argument Constructions (VACs) including those previously identified in the pattern grammar resulting from the COBUILD project. This generates (1) a list of verb types that occupy each construction. We next tally the frequency profiles of these verbs to produce (2) a frequency ranked type-token distribution for these verbs, and we determine the degree to which this is Zipfian. Since some verbs are faithful to one construction while others are more promiscuous, we next produce (3) a contingency-weighted list reflecting their statistical association. To test whether each of these measures is a step towards increasing the learnability of VACs as categories, following principles of associative learning, we examine 20 verbs from each distribution. Here we explore whether there is an increase in the semantic cohesion of the verbs occupying each construction using semantic similarity measures. From inspection, this seems to be so. We are developing measures of this using network measures of clustering in the verb-space defined by WordNet and Roget's Thesaurus.

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