Method for predicting multiple criminal names by using sequence generation network based on multilayer attention

The invention relates to a method for predicting multiple criminal names by using a sequence generation network based on multi-layer attention, which better realizes context content dependence betweentexts on the basis of fusing a neural network and an attention mechanism so as to more accurately extract multiple criminal names of text contents. An original data set is transformed based on a multi-criminal-name prediction model of a multi-layer attention mechanism (nested word-level and sentence-level attention mechanisms), and then association information among criminal names is fused into the model through logical connection among criminal law criminal names. According to the method, a legal provision extractor and a legal provision text encoder are added, legal provision information isintroduced, text information irrelevant to a criminal name is filtered out from an original text through attention operation, information representation of a text corresponding to the criminal name to be predicted is enhanced