Joint extraction method for named entities and relationships in judicial domain

A technology of named entity and relationship extraction, applied in information extraction and judicial fields, can solve the problems of not considering overlapping relationships, error propagation, lost connections, etc.

Pending Publication Date: 2021-08-06
北京航天情报与信息研究所
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Existing related research usually separates the two sub-tasks of entity extraction and relationship extraction, that is, through the pipeline mode. Although the pipeline framework has the flexibility to integrate different data sour

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  • Joint extraction method for named entities and relationships in judicial domain
  • Joint extraction method for named entities and relationships in judicial domain
  • Joint extraction method for named entities and relationships in judicial domain

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Embodiment Construction

[0043] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. 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.

[0044] The embodiment of the invention discloses a joint extraction method of named entities and relations in the judicial field.

[0045] 1. When labeling an entity, the label consists of four parts: entity boundary, entity category, relationship category, and entity location.

[0046] 1) Entity boundaries. The entity boundary adopts the "BIO" labeling principle, where B represents the initial character of each entity, I represents the middle or end characte...

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Abstract

The invention discloses a joint extraction method for named entities and relationships in a judicial domain, which is an entity relation extraction method of a BILSTM network and an attention mechanism set based on a BERT pre-training language model, realizes joint learning of two tasks through parameter sharing, and fully utilizes the relation between the tasks to optimize a result. A BERT pre-training language model is selected to train word vectors to complete conversion work of the data set word vectors; more complete context feature information is acquired by using a BILSTM neural network so as to extract text depth word vector features; Finally, category labels of the characters are acquired through a softmax classifier to realize entity recognition, and an association relationship is judged between the current character and the previous character by utilizing an attention mechanism to realize combined extraction of the entity and multiple relationships.

Description

technical field [0001] The invention relates to the technical field of information extraction, and more specifically relates to a joint extraction method of named entities and relationships in the judicial field. Background technique [0002] With the rapid development of the Internet and the explosive growth of information today, how to efficiently obtain the required information is a hot research issue, and information extraction technology has emerged as the times require. Information extraction can be subdivided into three subtasks: named entity recognition, entity relationship extraction, and event extraction. Obtaining semantic triples through entity recognition and entity relationship extraction is an important prerequisite for building knowledge graphs and understanding natural language. The judicial field is a typical knowledge-intensive industry. In the big data era of information explosion, laws and regulations, guiding cases, legal documents, etc. have emerged in...

Claims

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Application Information

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IPC IPC(8): G06F40/295G06F40/30G06F16/35G06N3/04
CPCG06F40/295G06F40/30G06F16/353G06N3/048G06N3/044
Inventor 毛松李振伟程佳张文静
Owner 北京航天情报与信息研究所
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