Sequence labeling method, device and equipment and readable storage medium

Abstract

The invention relates to the technical field of natural language processing, in particular to a sequence labeling method, device and equipment and a readable storage medium. The method is used for improving the accuracy of sequence labeling. The method comprises the following steps of: aiming at each segmented word contained in the to-be-identified statement, adopting a pre-trained character vector generation model and a preset word vector generation model to generate a first word vector and a second word vector corresponding to a segmented word are generated respectively, adopting a pre-trained weight coefficient and using the first word vector and the second word vector to generate a third word vector corresponding to the segmented word, and then adopting a pre-trained sequence labelingmodel to generate a sequence labeling result. Therefore, the word vectors are fused by adopting the pre-trained weight coefficient, and the third word vector generated by fusion is used as the input of the sequence labeling model, so that the processing process of sequence labeling is optimized, and the accuracy and the processing efficiency of sequence labeling are improved.

Description

technical field [0001] The present disclosure relates to the technical field of natural language processing, and in particular to a sequence labeling method, device, equipment and readable storage medium. Background technique [0002] Sequence tagging is a basic and important problem in natural language processing. It covers a wide range and can be used to solve a series of character classification problems, such as word segmentation, part-of-speech tagging, named entity recognition, relationship extraction, etc. [0003] At present, when performing sequence labeling, the feature method of word granularity is usually used for sequence labeling. However, only considering the feature mode of word granularity leads to a single dimension of sequence features, which leads to errors in sequence labeling, resulting in low accuracy of sequence labeling. [0004] It can be seen that a new solution needs to be designed to overcome the above-mentioned defects. Contents of the invent...

AI Technical Summary

Problems solved by technology

However, only the feature mode of word granularity is considered, resulting in a single dimension of sequence features, resulting in errors in sequence labeling, resulting in low accuracy of sequence labeling

Images