Natural language processing methods, devices, equipment, and computer-readable storage media

Abstract

This application provides a natural language processing method, apparatus, device, and computer-readable storage medium; relating to the field of artificial intelligence technology, the method includes: obtaining a hyperbolic word vector sequence based on a preset word vector table; performing attention encoding on the current hyperbolic word vector to obtain attention encoding features corresponding to the current hyperbolic word vector; performing a linear transformation on the attention encoding features through a preset Lorentz transformation function to obtain linear encoding features corresponding to the attention encoding features; the preset Lorentz transformation function is obtained by training a linear transformation matrix model that satisfies preset constraints; the preset constraints are used to ensure that the output feature vector obtained by the linear transformation matrix model after processing the input feature vector in the hyperbolic space is located in the hyperbolic space; and obtaining the target processing result corresponding to the sentence to be processed based on the linear encoding features. This application can improve the stability and efficiency of natural language processing using hyperbolic neural networks.

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