Knowledge base question-answering method and system in power field

Abstract

The invention provides a knowledge base question-answering method in the electric power field, which comprises the steps of performing part-of-speech tagging and syntactic analysis on acquired questions in the electric power field to obtain question expressions of the questions in the electric power field; identifying the question expression of the power field question based on a pre-constructed key phrase identification model to obtain a key entity and a key attribute phrase of the power field question; based on the key entities and the key attribute phrases, carrying out retrieval in a powerdomain knowledge base, and obtaining the question answers, wherein the key phrase recognition model comprises training open domain questions to obtain key entities and key attribute phrases corresponding to the open domain questions. According to the method and the system, high dependence of electric power domain model training on terms in the prior art is avoided, and knowledge base questions and answers in the electric power domain can be achieved only by utilizing easily obtained open domain resources.

Description

technical field [0001] The invention belongs to the fields of natural language processing and intelligent question answering, and in particular relates to a knowledge base question answering method and system in the electric power field. Background technique [0002] Domain-oriented knowledge base question answering technology is an important means to utilize knowledge information in this domain. Unlike traditional search engines that receive keywords as indexes, domain-specific knowledge base question answering technology receives natural language questions as the input of the system or device, and directly gives accurate and professional answers through domain knowledge base retrieval. The domain knowledge base question answering system or device can usually be used as an office assistant for a specific field, providing users with professional domain knowledge retrieval services, and has been widely used in work and life, such as: Microsoft's "Cortana", Alibaba's " Cube S...

AI Technical Summary

Problems solved by technology

However, handwriting templates is a process with high labor and time costs, especially for complex knowledge bases, it is difficult to cover all question forms or knowledge base content, and it is incomplete; the end-to-end method does not have a handwriting template process, The cost is low, but it usually requires a large amount of Q&A data related to the content of the knowledge base to train the model, which has strong domain dependence, but the Q&A data is difficult to obtain or organize

Images