A neural network-based knowledge graph inconsistency reasoning method, comprising the following steps: performing representation learning on a triplet by using a knowledge representation learning algorithm to obtain entity representations and a relationship representation and calculating a representation score; then using the entity representations and the relationship representation as an input of a neural network; modeling an axiom by means of the neural network by using the triplet to learn parameters of the neural network used for representing the corresponding axiom, thereby obtaining an axiom model; obtaining an axiom prediction value of the triplet by using the axiom model; and implementing determination of inconsistency of the triplet and the corresponding axiom on the basis of the representation score and the axiom prediction value of the triplet. In the method, there is no need to give ontology information, an inconsistency axiom is learned by using a neural network, and whether there is inconsistency in a triplet and whether there is inconsistency on the given axiom are determined by means of a knowledge representation learning algorithm and the neural network.
NEURAL NETWORK–BASED KNOWLEDGE GRAPH INCONSISTENCY REASONING METHOD