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Remote supervision entity relation joint extraction method and system based on multilayer LSTM (Long Short Term Memory)

An entity relationship and remote supervision technology, applied in biological neural network models, instruments, electrical and digital data processing, etc., can solve problems such as unsatisfactory entity relationship extraction effects.

Pending Publication Date: 2021-06-18
GUANGDONG UNIV OF TECH
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  • Application Information

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Problems solved by technology

[0003] The invention provides a multi-layer LSTM-based remote supervision entity relationship joint extraction method and system, which is used to solve the existing technical problem of unsatisfactory entity relationship extraction effect

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  • Remote supervision entity relation joint extraction method and system based on multilayer LSTM (Long Short Term Memory)
  • Remote supervision entity relation joint extraction method and system based on multilayer LSTM (Long Short Term Memory)
  • Remote supervision entity relation joint extraction method and system based on multilayer LSTM (Long Short Term Memory)

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Embodiment Construction

[0034] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is a part of embodiments of the present invention, but not all embodiments. 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.

[0035] For ease of understanding, see Figure 1 to Figure 3 , the present invention provides an embodiment of a multi-layer LSTM-based remote supervision entity relationship joint extraction method, including:

[0036] Step 101, using the Encyclopedia triplet as the external knowledge base and the news text of the marine economic industry text d...

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Abstract

The invention discloses a multi-layer LSTM-based remote supervision entity relationship joint extraction method and system, a data set is remotely supervised and manufactured by adopting an encyclopedia triple, and an entity relationship joint extraction model comprises a character LSTM layer, a coding layer, an entity extraction module and a relationship extraction module. The remote supervision data set is used for training the entity relation joint extraction model, the trained entity relation joint extraction model is used for entity relation joint extraction, the entity relation can be effectively recognized, and the technical problem that the existing entity relation extraction effect is not ideal is solved.

Description

technical field [0001] The present invention relates to the technical field of entity relationship extraction, in particular to a multi-layer LSTM-based remote supervision entity relationship joint extraction method and system. Background technique [0002] The joint extraction of entities and relations is the main task of building a knowledge graph, which is a challenging task, given a sentence of unstructured text to identify triples of two entities and their related relations. Identifying triplets is very challenging. One is the construction of data sets. It takes a lot of manpower and material resources to successfully produce data sets in professional fields. Second, given a sentence, there may be three types of triples in the sentence. Triple, the first is the normal case, in this case, there is only one relationship between two entities, and the entities do not overlap, the second type is EPO (EntityPairOverlay), similar entity pairs have neighbors and contain two ty...

Claims

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Application Information

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IPC IPC(8): G06F40/295G06F40/216G06F16/36G06N3/04
CPCG06F40/295G06F40/216G06F16/367G06N3/047G06N3/048G06N3/044
Inventor 程良伦马建文张伟文
Owner GUANGDONG UNIV OF TECH