Natural language automatic prediction inference method with interpretation generation

Abstract

The invention provides a natural language automatic prediction inference method with interpretation generation. The natural language automatic prediction inference method comprises the following steps: 1, training a variational interpretation generation model; 2, training an interpretation-based logic relationship prediction model; and 3, explaining and generating natural language inference through the variational explaining production model, and carrying out logic relationship prediction through the generated explaining.

Description

technical field [0001] The invention belongs to the field of natural language processing, in particular to an automatic prediction and inference method of natural language with explanation generation. Background technique [0002] With the continuous development of artificial intelligence technology, all areas of social production and life are undergoing tremendous changes. As one of the basic technologies for machines to understand human language, natural language inference has an increasing impact on all aspects of people's lives. Natural language inference refers to judging the logical relationship between the hypothetical text and it - implication, irrelevance or contradiction - given the premise text information. This technology supports many applications in the upper-level text field, and can help search engines locate content containing user search information in document collections, filter and screen information that is irrelevant or contradictory to search keyword...

AI Technical Summary

Problems solved by technology

Since logical information exists implicitly in premise-hypothesis text pairs, it is difficult for existing discriminative explanation generators to effectively capture and generate explanations containing correct logical semantics

[0008] In addition, although Camburu et al. [Camburu et al., 2018] designed a Siamese network-based attention mechanism for natural language inference, they still lack the interactive information between premises and hypotheses, which are often used in non-interpretable natural language Extensively proven to be very effective in inferring models

Images