Hedge detection is largely based on the identification of lexical items like suggest and might which indicate sentence level uncertainty.
we can then use the large amounts of unannotated sentences that are available to extract n-gram features that have high uncertainty class conditional probability and add them to our training set with those features labeled as hedges as described in Medlock and Briscoe (2007).