Construction of a FrameNet Labeler for Swedish Text

Abstract

We describe the implementation of a FrameNet-based semantic role labeling system for Swedish text. To train the system, we used a semantically annotated corpus that was produced by projection across parallel corpora. As part of the system, we developed two frame element bracketing algorithms that are suitable when no robust constituent parsers are available. Apart from being the first such system for Swedish, this is, as far as we are aware, the first semantic role labeling system for a language for which no role-semantic annotated corpora are available. The estimated accuracy of classification of pre-segmented frame elements is 0.75, and the precision and recall measures for the complete task are 0.67 and 0.47, respectively.

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