Word sense disambiguation is one of the first problems in natural language processing system so far． It trys to solve the problem
of word sense disambiguation in natural language processing by Sense Pruning using HowNet． We proposes that the objective of
WSD is to reduce the number of plausible meanings of a word as much as possible through“Sense Pruning”． After Sense Pruning，it
will associate a word with a list of plausible meanings． It would like to keep the truly correct sense of each word on its own meaning list．
Developing a human-machine mutual word sense tagging system and two set of criteria were used for the evaluation of Sense Pruning algorithm:
recall rate and reduction of the number of possible meanings of a sentence． Effects of the size of the analytical window and the
analytical unit were studied．