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.
REF developed a tree kernel-based system to resolve the scope of negation and speculation, which captures the structured information in syntactic parsing trees.
Tree Kernel-based Negation and Speculation Scope Detection with Structured Syntactic Parse Features
EMNLP
Computer Science