Semantic role labeling is the process of annotating the predicate-argument struc- ture in text with semantic labels. In this paper we present a state-of-the-art base- line semantic role labeling system based on Support Vector Machine classifiers. We show improvements on this system by: i) adding new features including fea- tures extracted from dependency parses, ii) performing feature selection and cali- bration and iii) combining parses obtained from semantic parsers trained using dif- ferent syntactic views. Error analysis of the baseline system showed that approx- imately half of the argument identifica- tion errors resulted from parse errors in which there was no syntactic constituent that aligned with the correct argument. In order to address this problem, we com- bined semantic parse...

Click Here to View the Paper In XML Format