Entity relationship extraction method

An extraction method and entity relationship technology, applied in the field of information extraction

Active Publication Date: 2018-12-07
SHANGHAI JIAO TONG UNIV
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  • Claims
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Problems solved by technology

[0005] The object of the present invention is to provide a kind of entity relationship extraction...

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Embodiment Construction

[0034] The entity relationship extraction method proposed in the present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments. Advantages and features of the present invention will be apparent from the following description and claims. It should be noted that all the drawings are in a very simplified form and use imprecise scales, and are only used to facilitate and clearly assist the purpose of illustrating the embodiments of the present invention.

[0035] Please refer to figure 1 , which is a flow chart of the entity relationship extraction method of the present invention. Such as figure 1 As shown, the entity relationship extraction method includes:

[0036] First, step S1 is performed to label the negative samples in the dataset (the dataset before labeling is referred to as NYT) according to the description information of the entity (at this time, a new dataset is formed after labeling, which is subse...

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Abstract

The invention provides an entity relation extraction method. The entity relation extraction method includes the steps of firstly, marking a negative sample in a data set according to the description information of the entity, so as to divide the negative sample into a real negative sample and an uncertain sample; then, providing the indeterminate sample relation label to construct a new training set; finally, extracting the relationship features of the new training set according to the bi-directional gating loop unit to obtain the entity relationship. By labeling the negative samples of the dataset according to the entity description information, the dataset is effectively optimized. A new training set is constructed by endowing the indeterminate sample relation label to improve the accuracy of the training set and further improve the precision of the relationship of the extracted entities.

Description

technical field [0001] The invention relates to the technical field of information extraction, in particular to an entity relationship extraction method. Background technique [0002] Relation extraction is the most direct method to obtain knowledge triples from plain text. Its principle is to give accurate relationship predictions after modeling and analyzing entity pairs and the sentences in which they are located. For example, the result of relation extraction for "Steve Jobs" and "Apple" in the sentence "Steve Jobs was the co-founder and CEO of Apple and Pixar" should be the knowledge triple [Steve Jobs,Founder,Apple]. Traditional relationship extraction models are based on supervised learning algorithms. However, supervised learning relationship extraction methods require high-quality manual labeling training sets, and cannot achieve complete automatic relationship extraction. In order to break through the limitation of relation categories in relation extraction, Stanf...

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Application Information

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IPC IPC(8): G06F17/30
Inventor 贾维嘉张新松李鹏帅刘天一
Owner SHANGHAI JIAO TONG UNIV
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