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Entity relationship extraction method and device

An entity relationship, relationship collection technology, applied in neural learning methods, special data processing applications, instruments, etc.

Active Publication Date: 2019-11-08
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention provides a method and device for extracting entity relations to solve the problem of extracting overlapping entity relations

Method used

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  • Entity relationship extraction method and device
  • Entity relationship extraction method and device
  • Entity relationship extraction method and device

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Embodiment Construction

[0063] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention , but not all examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0064] First of all, some terms used in the embodiments of the present invention are explained below to facilitate the understanding of those skilled in the art.

[0065] 1. Overlapping entity relationship means that there is more than one semantic relationship between a pair of entities. For example, A is B's 'wife', A is also B's 'friend', and 'wife' and 'friend' are overlapping entity...

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Abstract

The invention provides an entity relationship extraction method and device. The entity relationship extraction method comprises the following steps: training an SE-LSTM initialization network according to a manually labeled training sample set X0 and an entity relationship pair set ER0 to obtain a neural network model NN0, the entity relationship pair set ER0 being an output obtained by inputtingthe training sample set X0 into the SE-LSTM network; obtaining a training sample set Xi; obtaining an entity relationship pair set ERi according to the entity relationship pair set ER0 and the relationship set, the relationship set being constructed according to the training sample set X0, and elements in the relationship set being mutually overlapped entity relationships; according to the training sample set Xi and the entity relationship pair set ERi, training the SE-LSTM initialization network in turn to obtain a neural network model NNi, and obtaining a neural network model set composed ofthe neural network model NN0 and the neural network model NNi; and performing entity relationship extraction according to the neural network model set. Therefore, the extraction problem of the overlapping entity relationship is solved.

Description

technical field [0001] The invention relates to the technical fields of data processing and data mining, in particular to a method and device for extracting entity relationship. Background technique [0002] Information extraction refers to the process of extracting information such as entities, events, and relationships from a piece of natural language text, forming structured data and storing it in a database for user query and use. As the core task and important link in the fields of information extraction, natural language understanding, and information retrieval, entity relationship extraction can identify entities from text and extract semantic relationships between entities. Information extraction technology is mainly used in machine learning and natural language processing tasks, including the construction and completion of knowledge graphs, information retrieval, and question answering systems. [0003] An entity relationship is a semantic relationship between a pa...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06N3/044
Inventor 晋小玲郭方园
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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