Paper: Support Vector Machines Applied To The Classification Of Semantic Relations In Nominalized Noun Phrases

ACL ID W04-2610
Title Support Vector Machines Applied To The Classification Of Semantic Relations In Nominalized Noun Phrases
Venue Computational Lexical Semantics Workshop
Session
Year 2004
Authors

The discovery of semantic relations in text plays an important role in many NLP appli- cations. This paper presents a method for the automatic classification of semantic relations in nominalized noun phrases. Nominalizations represent a subclass of NP constructions in which either the head or the modifier noun is derived from a verb while the other noun is an argument of this verb. Especially designed fea- tures are extracted automatically and used in a Support Vector Machine learning model. The paper presents preliminary results for the se- mantic classification of the most representative NP patterns using four distinct learning mod- els.