Semantic Role Labeling with the Swedish FrameNet
Richard Johansson, Karin Friberg Heppin, Dimitrios Kokkinakis · 2012
Wepresent the first results onsemantic role labeling using the SwedishFrameNet, whichis a lexical resource currently indevelopment. Several aspects of the taskare investigated, including the selection of machine learning features, the effect of choice of syntactic parser, and the ability of the system to generalize to new frames and new genres. In addition, we evaluate two methods to make the role label classifier more robust: cross-frame generalization and cluster-based features. Although the small amount of training data limits the performance achievable at the moment, we reachpromising results. Inparticular, the classifierthat extracts theboundaries of arguments works well fornew frames,which suggests that italready at thisstage canbe useful inasemi-automatic setting. Keywords:Frame semantics, semantic role labeling, Swedish 1.