A FrameNet-Based Semantic Role Labeler for Swedish

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A FrameNet-Based Semantic Role Labeler for Swedish
We present a FrameNet-based semantic role labeling system for Swedish text. As training data for the system, we used an annotated corpus that we produced by transferring FrameNet annotation from the English side to the Swedish side in a parallel corpus. In addition, we describe two frame element bracketing algorithms that are suitable when no robust constituent parsers are available. We evaluated the system on a part of the FrameNet example corpus that we translated manually, and obtained an accuracy score of 0.75 on the classification of presegmented frame elements, and precision and recall scores of 0.67 and 0.47 for the complete task.
Richard Johansson, Pierre Nugues
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where ACL
Authors Richard Johansson, Pierre Nugues
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