Entity recognition method and device for text, electronic equipment and storage medium

Abstract

The invention provides a text entity recognition method and device, electronic equipment and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining a to-be-processed text, wherein the to-be-processed text is a mixed text of at least two languages; obtaining a clause tool according to the language category, and performing clause processing on the to-be-processed text through the clause tool to obtain a plurality of to-be-processed sentences; performing word segmentation processing on the to-be-processed sentences to obtain a plurality of to-be-processed segmented words, and splicing the to-be-processed segmented words into a character string with a target length; and when the target length is greater than a preset length threshold, performing matching annotation on the plurality of to-be-processed segmented words based on entries of the dictionary to obtain an entity identification result. Therefore, entity recognition of the multi-language mixed text is realized, and the accuracy of entity recognition of the overlong text can be improved.

Description

technical field [0001] The present application relates to the technical field of data processing, and in particular to a text entity recognition method, device electronic equipment and a storage medium. Background technique [0002] At present, with the continuous development of the medical and health field, data from different sources and in different formats in the medical and health field continue to emerge, and a large amount of information that can be identified and mined is hidden in these big data. As the most important step in medical data analysis, medical entity recognition (especially disease entity recognition) can extract medical terms existing in related texts, which plays an important role in subsequent research. Due to different problems in medical texts from different sources, for example: Chinese-based medical literature is often mixed with English descriptions of disease words, target words, etc.; medical patent texts often have long description sentences,...

AI Technical Summary

Problems solved by technology

[0005] For this reason, the first purpose of this application is to propose a text entity recognition method to realize entity recognition of multilingual mixed texts, and to improve the accuracy of entity recognition for overly long texts, and to solve problems in the prior art. For ultra-long sentences, the input text data is truncated and cannot be fully recognized, and the recognition results are not accurate enough.

Images