Natural language labeling method based on artificial intelligence and related equipment

A natural language and artificial intelligence technology, applied in natural language data processing, semantic analysis, unstructured text data retrieval, etc., can solve problems such as the inability to quickly label training corpus

Active Publication Date: 2020-10-30
CHINA PING AN LIFE INSURANCE CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to solve the problem that the training corpus cannot be marked quickly at present

Method used

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  • Natural language labeling method based on artificial intelligence and related equipment
  • Natural language labeling method based on artificial intelligence and related equipment
  • Natural language labeling method based on artificial intelligence and related equipment

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Embodiment Construction

[0085] Embodiments of the present invention provide an artificial intelligence-based natural language tagging method and related equipment. In this solution, efficient tagging of natural language texts can be improved, and time and cost of manual tagging can be reduced.

[0086] The terms "first", "second", "third", "fourth", etc. (if any) in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and not necessarily Used to describe a specific sequence or sequence. It is to be understood that the terms so used are interchangeable under appropriate circumstances such that the embodiments described herein can be practiced in sequences other than those illustrated or described herein. Furthermore, the term "comprising" or "having" and any variations thereof, are intended to cover a non-exclusive inclusion, for example, a process, method, system, product or device comprising a sequence of steps or elements is not necessa...

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Abstract

The invention relates to the field of artificial intelligence, and discloses a natural language labeling method based on artificial intelligence and related equipment. The method comprises the steps of obtaining a to-be-labeled natural language text; through a pre-trained sequence labeling model, carrying out semantic coarse-grained sequence labeling on the sequence labeling model to obtain a labeling sequence; determining a target word in a natural language text according to the labeling sequence, and determining a target role type of the target word; obtaining a preset template word corresponding to the target role type, and calculating a similarity value between the preset template word and the target role type; and according to the similarity value and a preset sub-category judgment rule, determining a sub-category corresponding to the target word as a target sub-category, and performing semantic fine-grained sequence labeling on the natural language text to obtain a labeled text.In addition, the invention further relates to a blockchain technology, and the natural language text to be labeled and/or the labeled text can be stored in the blockchain. According to the method, thecorpus annotation efficiency for language model training can be improved.

Description

technical field [0001] The invention relates to the field of artificial intelligence, in particular to an artificial intelligence-based natural language tagging method and related equipment. Background technique [0002] With the vigorous development of deep learning technology, there are also in-depth applications in natural language processing. The trained model can perform word segmentation, understanding, and even emotion classification of natural language to understand the intent of the sentence. The training of the model requires a large number of labeled sentence samples. Currently, two types of deep learning models are mainly used for semantic understanding. One is semantic understanding with supervised learning, and the other is semantic understanding that combines semi-supervised learning, rule writing, and pre-trained word vectors. However, both the former and the latter require a large number of labeled sentences. In terms of intent recognition, the higher th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F40/30G06F40/205G06F40/186G06F40/169G06F16/35
CPCG06F40/30G06F40/205G06F40/186G06F40/169G06F16/355
Inventor 勾震马丹曾增烽
Owner CHINA PING AN LIFE INSURANCE CO LTD
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