Dependency semantic-based Chinese unsupervised open entity relationship extraction method

Abstract

The invention relates to a dependency semantic-based Chinese unsupervised open entity relationship extraction method. The method comprises the following steps of preprocessing an input text: performing Chinese word segmentation, part-of-speech tagging and dependency grammar analysis on the input text; performing named entity identification on the input text; arbitrarily selecting two entities from identified entities to form candidate entity pairs; searching for a dependency path between two entities in the candidate entity pairs; and analyzing whether a syntactic structure mapped by the dependency path is matched with a normal form of a dependency semantic normal form set or not, if yes, extracting words or phrases from the residual part of the input text according to the matched normal form to serve as relational words, forming a relational triple by the extracted relational words and the candidate entity pairs, and if not, performing normal form matching of a next group of the candidate entity pairs; and outputting the relational triple. Compared with the prior art, the method has the advantages that the calculation complexity is low; the extraction efficiency is high; distance position limitation is overcome; a simple sentence also can be extracted and the like.

Description

technical field [0001] The invention relates to information extraction research in the fields of artificial intelligence and natural language processing, in particular to a Chinese unsupervised open entity relationship extraction method based on dependency semantics. Background technique [0002] The wave of big data seems to be surging like the Qiantang River, and the data accumulated on the Internet is growing explosively. Faced with the massive amount of information on the web, it becomes very difficult for users to quickly find the information they care about. Traditional search engines can only return a large number of webpages related to the user's query content to the user, and the information that the user needs can only be obtained after browsing the webpage. This single search method of returning webpages can no longer meet the actual needs of users facing massive network data. The Internet provides people with an inexhaustible source of information, how to quick...

AI Technical Summary

Problems solved by technology

The purpose of the present invention is to avoid the disadvantages of traditional extraction methods such as high requirements for training corpus, poor portability and scalability, and inability to adapt to open network texts, and the extraction method under the English corpus due to the complex and flexible characteristics of Chinese in terms of morphology and grammar. Unable to be transplanted to Chinese, this invention proposes an open unsupervised entity relationship extraction method for network text based on the characteristics of Chinese language

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