Tree Kernel-based Negation and Speculation Scope Detection with Structured Syntactic Parse Features

Bowei Zou, Guodong Zhou, Qiaoming Zhu

Abstract: Scope detection is a key task in information extraction. This paper proposes a new approach for tree kernel-based scope detection by using the structured syntactic parse information. In addition, we have explored the way of selecting compatible features for different part-of-speech cues. Experiments on the BioScope corpus show that both constituent and dependency structured syntactic parse features have the advantage in capturing the potential relationships between cues and their scopes. Compared with the state of the art scope detection systems, our system achieves substantial improvement.