Entity linking method and device, equipment and storage medium

Abstract

The invention provides an entity linking method and device, equipment and a storage medium, and relates to the field of natural language processing and knowledge maps. The specific implementation scheme comprises the steps: obtaining a plurality of candidate entities related to mention based on a knowledge base, and obtaining a plurality of mention candidate entity pairs; respectively carrying out feature extraction processing on the mention and the candidate entities to obtain mention features and candidate entity features of each mention candidate entity pair; based on the mention feature and the candidate entity feature of each mention candidate entity pair, constructing a dynamic hypergraph, and performing disambiguation processing by using the dynamic hypergraph to obtain a target entity corresponding to the mention. According to the technical scheme provided by the invention, the training time of the neural network is shortened, and the high-level semantic association between the mention and the candidate entity is deeply mined, so that the accuracy and recall rate of the entity linking task are improved.

Description

technical field [0001] The present disclosure relates to the technical field of artificial intelligence, in particular to the fields of natural language processing and knowledge graph. Background technique [0002] In related technologies, the entity linking method based on the graph neural network usually has a large amount of parameters and is difficult to train, and there are also problems such as less training resources, more data noise, and entity knowledge base updating over time, which affects the accuracy of the entity linking task. and recall rate. Contents of the invention [0003] The present disclosure provides a method, device, device and storage medium for entity linking. [0004] According to an aspect of the present disclosure, a method for linking entities is provided, including: [0005] Based on the knowledge base, obtain multiple candidate entities related to the mention, and obtain multiple mention candidate entity pairs; [0006] Perform feature ex...

AI Technical Summary

Problems solved by technology

[0002] In related technologies, the entity linking method based on graph neural network usually has a large amount of parameters and is difficult to train, and there are also problems such as less training resources, more data noise, and entity knowledge base updating over time, which affects the accuracy of entity linking tasks and recall

Images