The invention provides a machine reading inference method based on a graph neural network. Overall process is as follows: a proposition judgment module, an entity identification module and an entity chain finger module are obtained through secondary training of a neural network; an information extraction module and a polarity discrimination module are combined respectively; a fact logic relation graph in a reading material and entity and polarity information in a to-be-inferred proposition are obtained, and then the fact logic relation graph, together with an environment knowledge graph, is input into a graph neural network subjected to secondary training together to obtain a final entity logic relation graph; and finally an inference conclusion and an inference route graph are obtained byusing a Bayesian network. According to the method, the graph neural network is applied to machine reading inference for the first time; on the basis of relation inference, the machine logic inferencecapacity is further given, and the automatic case inference process is achieved; and the method has important use value in the fields of criminal investigation, machine questioning and answering andthe like.