Data annotation method and device

Abstract

The invention discloses a data annotation method. The method comprises the steps that initial annotation information of target data input by different initial users is acquired through an initial terminal; whether or not the acquired initial annotation information is identical is judged; if not, the acquired initial annotation information is transmitted to a first audit terminal, first audit annotation information of the target data input by a first audit user according to the acquired initial annotation information is acquired through the first audit terminal, and the first audit annotation information is determined as final annotation information of the target data and stored. Therefore, when multiple annotation personnel have difference on annotation results of the same data, annotationspecialists or authority annotation specialists determine the optimum annotation result of the data quickly, the efficiency and accuracy of data annotation are improved, and the method helps to increase the service level of the annotation personnel and improve the accuracy of stored annotation information. Correspondingly, the invention discloses a data annotation device, equipment and a computerreadable storage medium which have the advantages above.

Description

technical field [0001] The present invention relates to the technical field of natural language labeling, and more specifically, to a data labeling method, device, equipment and computer-readable storage medium. Background technique [0002] With the continuous development of Internet technology and computer science and technology, artificial intelligence is intensifying, and natural language processing is an important research direction in artificial intelligence, which integrates linguistics, computer science, mathematics and other disciplines. Natural language processing is to realize natural language communication between humans and computers, or to realize natural language understanding and natural language generation. Since natural language texts and dialogues have extensive ambiguity and polysemy at all levels, it is necessary to manually annotate natural language to provide effective convenience for natural language processing. [0003] At present, when performing m...

AI Technical Summary

Problems solved by technology

However, when there are differences in the labeling results of the same data by multiple labelers, the best labeling results can only be determined through collective discussion or manual selection, which may stagnate the labeling work, reduce labeling efficiency, and is not conducive to The improvement of the professional level of labeling personnel; at the same time, the accuracy of inventory labeling information cannot be improved

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