While these techniques have indeed shown to reduce the cost of training, they are typically limited by availability of the existing data as the reliability of annotation propagation suffers when sentences are not similar enough.
in this paper we focus on how to automatically generate high quality training data for Adverse Drug Reaction detection with minimal human supervision and costs.