Paper: A FrameNet-Based Semantic Role Labeler For Swedish

ACL ID P06-2057
Title A FrameNet-Based Semantic Role Labeler For Swedish
Venue Annual Meeting of the Association of Computational Linguistics
Session Poster Session
Year 2006
Authors

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 par- allel 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 trans- lated manually, and obtained an accuracy score of 0.75 on the classification of pre- segmented frame elements, and precision and recall scores of 0.67 and 0.47 for the complete task.