We start with a detailed introduction of the framework, describing the averaged perceptron algorithm (Collins, 2002) and its efficient implementation issues <cite>(Zhang and Clark, 2007)</cite> , as well as beam-search and the early-update strategy (Collins and Roark, 2004) . We then illustrate how the framework can be applied to NLP tasks, including word segmentation, joint segmentation & POS-tagging, labeled and unlabeled dependency parsing, joint POS-tagging and dependency parsing, CFG parsing, CCG parsing, and joint segmentation, POS-tagging and parsing.