Riley induces a decision tree for sentence boundary detection using the following features (Riley 1989, pages 351 and 352): The resulting decision tree is able to classify the periods in the Brown corpus with a very low error rate of only 0.2%, which is 0.82% better than that achieved by Punkt.
the impressive performance of Riley's approach also requires impressive amounts of training data: He calculated the probabilities that a certain word occurs before or after a sentence boundary from 25 million words of AP newswire text.