Support vector machines applied to the classification of semantic relations in nominalized noun phrases
Roxana Gîrju, Ana-Maria Giuglea, Marian Olteanu, Ovidiu Fortu, Orest Bolohan, DAN I. MOLDOVAN · 2004
The discovery of semantic relations in text plays an important role in many NLP applications. 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 features are extracted automatically and used in a Support Vector Machine learning model. The paper presents preliminary results for the semantic classification of the most representative NP patterns using four distinct learning models.