In this paper, we propose a Convolutional Neural Network (CNN)-based model with probabilistic weighted average pooling to address speculation and negation scope detection.
our CNN-based model extracts those meaningful features from various syntactic paths between the cues and the candidate tokens in both constituency and dependency parse trees.