Model training method, device, equipment and storage medium

Abstract

The present disclosure relates to a model training method, device, device, and storage medium. The method includes: using a language model trained based on entities in a knowledge map to perform character prediction on input text; and extracting entities from the input text after character prediction is completed. ; Predict the extracted entity to obtain whether the extracted entity belongs to the entity in the knowledge graph. The recognition accuracy of entities can be improved through the model training method provided in the present disclosure.

Description

technical field [0001] The present disclosure relates to the field of information technology, and in particular to a model training method, device, equipment and storage medium. Background technique [0002] With the continuous development of science and technology, the language model occupies an important position in natural language processing, and its task is to predict the probability of a sentence appearing in the language. [0003] However, the inventors of the present application found that the language model in the prior art is obtained through text training, so that the trained language model cannot accurately understand and infer the connotation of entities in the text. Contents of the invention [0004] In order to solve the above technical problems or at least partly solve the above technical problems, the present disclosure provides a model training method, device, equipment and storage medium, and the recognition accuracy of entities can be improved by the mo...

AI Technical Summary

Problems solved by technology

[0003] However, the inventors of the present application found that the language model in the prior art is obtained through text training, resulting in the inability of the trained language model to accurately understand and infer the connotation of entities in the text

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