Extraction of Poetic and Non-Poetic relations from of-Prepositions using WordNet

The main goal of this paper is to extract the semantic relations underpinning concepts English prepositional of-constructions derived from poetic and non-poetic datasets, using Princeton WordNet. problem addressed by two different algorithms, which are evaluated for their ability model types resources derived, predict unseen relations. first algorithm introduces concept subsumption hierarchy between in order derive most general associated each type data source identify a set specific dataset. second investigates use weighting scheme establish importance association extracted. Of particular notions hierarchies (expressed as synset pairs) Inverse Relation Frequency (IRF) measure, inspired Document measure used Information Retrieval. ontological prospects WordNet above algorithms creation ontologies also briefly discussed. Although interest proposed methods lies identification conceptual resources, followed can be applied on other domains too.