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Entity relationship extraction method and system in text, storage medium, and electronic device

A technology of entity relationship and entity, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as wrong labeling, and achieve the effect of solving the problem of wrong labeling

Active Publication Date: 2019-03-15
SOUTH CHINA NORMAL UNIVERSITY
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  • Claims
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AI Technical Summary

Problems solved by technology

[0003] Based on this, the purpose of the present invention is to provide a method for extracting entity relationship in text, which uses semantic context information in text to extract the relationship between entities, and fundamentally solves the problem of wrong labeling in the remote supervision process

Method used

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  • Entity relationship extraction method and system in text, storage medium, and electronic device
  • Entity relationship extraction method and system in text, storage medium, and electronic device
  • Entity relationship extraction method and system in text, storage medium, and electronic device

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Embodiment Construction

[0051] see figure 1, in one embodiment, the entity relationship extraction method in the text of the present invention includes the following steps:

[0052] Step S101: Obtain entity triplet relationship set, entity and entity attribute set, and concept set.

[0053] In this embodiment, Freebase is selected as the basic knowledge base. Freebase is a large-scale knowledge graph, which inherently contains more than 7,300 relationships and more than 900 million entities. The Resource Description Framework (ResourceDescription Framework, RDF) triplet (entity 1, relationship, entity 2) in Freebase is arranged and stored in the computer, as the entity triplet relationship set of the present embodiment, denoted as R, including for example A triple like (New York, CityOf, United States). In addition, the entities and entity attribute information in Freebase are sorted and stored in the computer, as the entity and entity attribute set in this embodiment, denoted as E, and each entit...

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Abstract

The invention relates to a method and a system for extracting entity relations from texts, a storage medium and an electronic device. The method comprises the following steps: acquiring entity triplerelation set, entity and entity attribute set, and concept set; Training a triple relation set of a sentence of a text set and two entities identified in the sentence; Obtaining a sentence comprisinga training text set, two entities identified in the sentence, concepts corresponding to the two entities and a relation set of the two entities respectively, inputting sentence vectors into an entityrelation extraction model and training; Each sentence contains two entities, concepts corresponding to the two entities, and a set of relationships between the two entities. The entity relationship extraction method of the invention extracts the relationship between entities by using the semantic context information in the text, and solves the error labeling problem existing in the remote monitoring process.

Description

technical field [0001] The invention relates to the technical field of text processing and information extraction, in particular to a method and system for extracting entity relations in text, a storage medium, and electronic equipment. Background technique [0002] In the past, people built some large-scale knowledge bases based on real-world knowledge, such as Wikipedia and DBpedia. These knowledge bases are widely used in the fields of artificial intelligence and natural language processing, such as question answering systems, information extraction, etc. The knowledge base contains a large number of triplet facts, for example (New York, CityOf, United States) represents the fact that "New York is a city in the United States". However, the existing knowledge base contains limited and far from complete facts, and new facts are generated every day. How to mark new facts to complete the knowledge base has become an urgent problem to be solved. It is a time-consuming and l...

Claims

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Application Information

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IPC IPC(8): G06F17/27
CPCG06F40/205G06F40/289G06F40/295G06F40/30
Inventor 蒋运承瞿荣朱星图郑一东马文俊詹捷宇刘宇东
Owner SOUTH CHINA NORMAL UNIVERSITY
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