Paper: A Cross-lingual Annotation Projection Approach for Relation Detection

ACL ID C10-1064
Title A Cross-lingual Annotation Projection Approach for Relation Detection
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2010
Authors

While extensive studies on relation ex- traction have been conducted in the last decade, statistical systems based on su- pervised learning are still limited because they require large amounts of training data to achieve high performance. In this pa- per, we develop a cross-lingual annota- tion projection method that leverages par- allel corpora to bootstrap a relation detec- tor without significant annotation efforts for a resource-poor language. In order to make our method more reliable, we intro- duce three simple projection noise reduc- tion methods. The merit of our method is demonstrated through a novel Korean re- lation detection task.