UNITN: Part-Of-Speech Counting in Relation Extraction

This report describes the UNITN system, a Part-Of-Speech Context Counter, that participated at Semeval 2010 Task 8: MultiWay Classification of Semantic Relations Between Pairs of Nominals. Given a text annotated with Part-of-Speech, the system outputs a vector representation of a sentence containing 20 features in total. There are three steps in the system’s pipeline: first the system produces an estimation of the entities’ position in the relation, then an estimation of the semantic relation type by means of decision trees and finally it gives a predicition of semantic relation plus entities’ position. The system obtained good results in the estimation of entities’ position (F1=98.3%) but a critically poor performance in relation classification (F1=26.6%), indicating that lexical and semantic information is essential in relation extraction. The system can be used as an integration for other systems or for purposes different from relation extraction.