Mining of Parsed Data to Derive Deverbal Argument Structure

Abstract

The availability of large parsed corpora and improved computing resources now make it possible to extract vast amounts of lexical data. We describe the process of extracting structured data and several methods of deriving argument structure mappings for deverbal nouns that significantly improves upon non-lexicalized rule-based methods. For a typical model, the F-measure of performance improves from a baseline of about 0.72 to 0.81.