Unsupervised Mapping of Arguments of Deverbal Nouns to Their
  Corresponding Verbal Labels
Aviv Weinstein Yoav Goldberg
Deverbal nouns are nominal forms of verbs commonly used in written English
texts to describe events or actions, as well as their arguments. However, many
NLP systems, and in particular pattern-based ones, neglect to handle such
nominalized constructions. The solutions that do exist for handling arguments
of nominalized constructions are based on semantic annotation and require
semantic ontologies, making their applications restricted to a small set of
nouns. We propose to adopt instead a more syntactic approach, which maps the
arguments of deverbal nouns to the universal-dependency relations of the
corresponding verbal construction. We present an unsupervised mechanism --
based on contextualized word representations -- which allows to enrich
universal-dependency trees with dependency arcs denoting arguments of deverbal
nouns, using the same labels as the corresponding verbal cases. By sharing the
same label set as in the verbal case, patterns that were developed for verbs
can be applied without modification but with high accuracy also to the nominal
constructions.