A Chinese named entity recognition method based on pinyin enhancement

By obtaining the pinyin grid embedding vector and word representation vector, and using the dilated convolutional neural network and MLP predictor to calculate the character fusion features of Chinese text, the problems of fuzzy character boundaries and entity segmentation errors in Chinese named entity recognition are solved, achieving more efficient named entity recognition.

CN120317255BActive Publication Date: 2025-10-10NAT UNIV OF DEFENSE TECH
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Patent Information

Application Number
CN202510788621.9
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-06-13
Publication Date
2025-10-10
Estimated Expiration
2045-06-13

AI Technical Summary

Technical Problem

Existing Chinese named entity recognition methods based on pinyin enhancement face problems such as fuzzy character boundaries, entity segmentation errors and difficulty in extracting semantic features in Chinese texts, resulting in low recognition performance.

Method used

By obtaining the two-dimensional pinyin grid embedding vector and word representation vector of the text to be recognized, a two-dimensional dilated convolutional neural network and an MLP predictor are used to calculate the fusion features and prediction scores between characters, and combined with the Biaffine classifier to improve the accuracy and efficiency of named entity recognition.

Benefits of technology

It improves the accuracy and efficiency of Chinese named entity recognition, solves the problems of fuzzy character boundaries and entity segmentation errors in Chinese text, and achieves more efficient entity recognition.

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Abstract

The application discloses a Chinese named entity recognition method based on pinyin enhancement, and the method comprises the following steps: obtaining a two-dimensional pinyin grid embedding vector and a word representation vector of a text to be recognized; projecting based on the word representation vector to obtain a two-dimensional grid feature vector; calculating a fusion feature between any two characters of the text to be recognized based on the pinyin grid embedding vector and the two-dimensional grid feature vector; calculating a first corresponding prediction score vector based on the fusion feature between any two characters by fusing the pinyin grid embedding vector and the two-dimensional grid feature vector; calculating a second corresponding prediction score vector based on the word representation vector; calculating a total prediction score vector based on the first corresponding prediction score vector and the second corresponding prediction score vector; and outputting the named entity of the text to be recognized based on the total prediction score vector, so that the efficiency of the Chinese named entity recognition based on pinyin enhancement is improved.
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