Corpus labeling method and device, server and storage medium

Abstract

The embodiment of the invention relates to the technical field of information processing, in particular to a corpus labeling method and device, a server and a storage medium. The corpus annotation method comprises the steps of acquiring an even number of manual annotation results of an initial corpus and a model annotation result of the initial corpus, wherein the model annotation result of the initial corpus is obtained according to a preset annotation model, and the preset annotation model is obtained by training a plurality of manually annotated initial corpora; and obtaining a unique labeling result meeting a preset condition from all labeling results including the manual labeling result and the model labeling result, and taking the labeling result as a final labeling result of the initial corpus. According to the embodiment of the invention, the high-quality corpus annotation result of the initial corpus can be obtained, and the influence of a single annotator on the corpus annotation quality is reduced.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of information processing, and in particular to a corpus tagging method, device, server and storage medium. Background technique [0002] Natural language processing refers to the computer receiving input in the form of natural language, and internally processes and calculates the natural language through user-defined algorithms to return the results expected by the user. It can usually be applied to fields such as text retrieval, machine translation, and information question answering. Users usually define the algorithm by establishing an algorithm model, and the established algorithm model needs to be trained through a large number of labeled original language materials; labeling the original language materials refers to processing the original corpus, and combining various representations of language features The additional codes are marked on the corresponding language component...

AI Technical Summary

Problems solved by technology

[0003] However, the inventors found that there are at least the following problems in the related technologies: in the traditional corpus labeling method, a single corpus is generally marked by a single labeler, and the cognitive level and operating habits of the labeler greatly affect the quality of labeling the corpus. As a result, the labeling results of the corpus are single, and it is difficult to judge the accuracy of the labeling results

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