Knowledge graph construction method and device, electronic equipment and storage medium

Abstract

The invention discloses a knowledge graph construction method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a target text to be subjected to named entity recognition; on the basis of preset attribute information of a plurality of preset entities, labeling each word in the target text to obtain a labeling data set including labeling data of each word; obtaining a named entity recognition result of the target text according to the annotation data set; according to the named entity recognition result, preprocessing all entities corresponding to different attribute information; according to a preset rule, classifying the entities according to different levels; and constructing a knowledge graph corresponding to the target text by using the entities of different levels, and storing the knowledge graph. According to the embodiment of the invention, the workload of workers and the information extraction difficulty are reduced, so that the information extraction efficiency and accuracy can be improved, and the labor cost and the time cost are reduced.

Description

technical field [0001] The present application relates to the field of computers, and in particular to a knowledge graph construction method, device, electronic equipment and storage medium. Background technique [0002] At present, when analyzing and evaluating the recorded text content, it usually requires the corresponding staff to perform manual operations based on the analysis and evaluation experience, etc., and the text content cannot be screened automatically, which increases the workload and difficulty of the staff , not only increases the labor cost, but also reduces the work efficiency and the accuracy of the analysis results. [0003] The relevant text information extraction technology can automatically extract text keywords, search topics or extract corresponding information for fixed-structure text content. Due to the limitations of applicable scenarios, it cannot meet the needs of extracting and evaluating more forms of text content. [0004] For the above pr...

AI Technical Summary

Problems solved by technology

[0002] At present, when analyzing and evaluating the recorded text content, it usually requires the corresponding staff to perform manual operations based on the analysis and evaluation experience, etc., and the text content cannot be screened automatically, which increases the workload and difficulty of the staff , which not only increases the labor cost, but also reduces the work efficiency and the accuracy of the analysis results

[0003] Relevant text information extraction technology can automatically extract text keywords, search topics or extract corresponding information for fixed-structure text content. Due to the limitations of applicable scenarios, it cannot meet the extraction and evaluation requirements for more forms of text content.

[0004] For the above problems, no effective solution has been proposed

Images