NUS-I2R: Learning a Combined System for Entity Linking.

Abstract

In this paper, we report the joint participation of NUS and I2R team in Knowledge Base Population at Text analysis conference 2010. For Entity Linking, we analyze IR approaches and SVM classification in the disambiguation stage and develop a supervised learner for combining these approaches. The combined system performs better than the individual components and achieves results much better than the median. Furthermore, according to our error analysis, quite some errors are caused due to the different Wikipedia version is used, which hinder our system to show significant better performance.