A FrameNet-based semantic role labeler for Swedish
Author
Summary, in English
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.
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.
Publishing year
2006
Language
English
Pages
436-443
Publication/Series
COLING/ACL 2006, 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
Document type
Conference paper
Publisher
Association for Computational Linguistics
Topic
- Computer Science
Keywords
- Natural Language Semantics
- Natural Language Processing
- Semantic Role Labeling
Conference name
COLING/ACL 2006, 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics
Conference date
2006-07-17 - 2006-07-21
Conference place
Sydney, Australia
Status
Published