@inProceedings{johansson-2012-atomic-156993, title = {Non-atomic Classification to Improve a Semantic Role Labeler for a Low-resource Language}, abstract = {Semantic role classification accuracy for most languages other than English is constrained by the small amount of annotated data. In this paper, we demonstrate how the frame-to-frame relations described in the FrameNet ontology can be used to improve the performance of a FrameNet-based semantic role classifier for Swedish, a low-resource language. In order to make use of the FrameNet relations, we cast the semantic role classification task as a non-atomic label prediction task. The experiments show that the cross-frame generalization methods lead to a 27% reduction in the number of errors made by the classifier. For previously unseen frames, the reduction is even more significant: 50%. }, booktitle = {Proceedings of the First Joint Conference on Lexical and Computational Semantics (*SEM); June 7-8; Montréal, Canada}, author = {Johansson, Richard}, year = {2012}, publisher = {Association for Computational Linguistics}, address = {Montréal, Canada}, }