Information extraction method based on artificial intelligence, storage medium and related device

Abstract

The embodiment of the invention discloses an information extraction method based on artificial intelligence, a storage medium and a related device, and is applied to the technical field of informationprocessing of artificial intelligence. For each sentence of a short text in a to-be-processed document, the information extraction method firstly determines relationship attributes contained in the short text according to a preset relationship classification model, then extracts entity pairs corresponding to the relationship attributes according to a preset entity extraction model, and can form triple information corresponding to each sentence of the short text. Practice proves that triple information of the to-be-processed document can be accurately obtained in the mode that the relation attributes and the entity pairs corresponding to the relation attributes are determined through different machine learning models, and transfer learning can be carried out due to the fact that the machine learning models are adopted for information extraction.

Description

technical field [0001] The present invention relates to the technical field of information processing based on artificial intelligence, in particular to an information extraction method, storage medium and related devices based on artificial intelligence. Background technique [0002] Information extraction refers to the extraction of triplet information in any document in a certain way, that is, <subject (Subject), attribute (Predicate), answer (Object)>, which is an important part of building a knowledge map, and the final knowledge map can be applied In the process of user interaction such as question answering, dialogue and retrieval. There are generally three types of data sources for information extraction, namely structured data, semi-structured data, and unstructured data. In the real world, the structured and semi-structured data that operators can quickly provide are limited, and a large amount of data is based on unstructured data. Existing in various forms...

AI Technical Summary

Problems solved by technology

[0003] An existing information extraction method mainly extracts relations through rule design, but rule exhaustion is limited, the coverage rate is low, rule conflicts or redundancy are prone to occur, and the extraction effect is far from enough

Another method of information extraction based on machine learning uses the Natural Language Processing (NLP) system to perform part-of-speech tagging and syntactic analysis on the data to be processed, to obtain the feature information of the data to be processed, and then to classify the relationship. This method can automatically classify relationships, but the performance depends on the quality of feature extraction, and the effect is not very stable.

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