Pattern self-learning based Chinese open relationship extraction method

An open and relational technology, applied in special data processing applications, instruments, electrical and digital data processing, etc., can solve the problems of reducing the accuracy of relational patterns, the recall rate of relational tuples is difficult to meet practical applications, and prone to errors. The results of relation extraction are reliable, and the accuracy and recall rate of entity relation extraction are good.

Inactive Publication Date: 2015-12-09
UNIV OF ELECTRONIC SCI & TECH OF CHINA
View PDF3 Cites 39 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Some existing relational extraction methods based on dependency analysis mainly pre-define limited relational patterns and then extract relational tuples, so the recall rate of extracted relational tuples is difficult to meet the practical application
At the same time, there are also some open relati

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Pattern self-learning based Chinese open relationship extraction method
  • Pattern self-learning based Chinese open relationship extraction method
  • Pattern self-learning based Chinese open relationship extraction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0018] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, 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 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.

[0019] figure 1 It is an embodiment of the present invention, that is, an overall flow chart of a Chinese open relation extraction method based on pattern self-learning disclosed in the present invention. Such as figure 1 As shown, the open relation extraction method provided in this embodiment may specifically include the following steps: ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

Open Chinese entity relationship extraction refers to, on the premise of not limiting a corpus field and a relationship category, automatic extraction of relationship information between entities from a Chinese corpus to obtain an entity relationship tuple. The present invention discloses a pattern self-learning based Chinese opening relationship extraction method. The method comprises the following three main steps of: firstly, based on an existing knowledge library, acquiring a high-quality entity relationship tuple and a corresponding sentence as a training corpus, and obtaining a dependent path mode between an entity and a relationship word by a pattern learning method proposed by the present invention; secondly, performing pre-processing of word segmentation, part-of-speech tagging, dependency analysis and the like on a to-be-extracted text, and performing entity relationship extraction by means of a relationship mode obtained by previous learning; and finally, performing quality evaluation on an entity relationship extracted automatically from the Chinese corpus by using a machine learning method, and obtaining the high-quality entity relationship tuple.

Description

technical field [0001] The invention relates to the field of natural language processing, in particular to Chinese information extraction and open Chinese relation extraction. Background technique [0002] Open relational extraction refers to automatically extracting entities and semantic relations between entities from text, without pre-defining relation types, and directly using words in the text as entity and relational words in relational tuples. For example, from the following example sentence "Obama graduated from Columbia University", the following ternary relational tuple can be extracted: (Obama, graduated, Columbia University). Open entity relationship extraction is the basis of knowledge base construction, and it has very important practical application value for intelligent information retrieval and application. [0003] Open relation extraction methods are mainly divided into three types, namely methods based on part of speech, methods based on semantic role la...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F17/27
Inventor 刘峤刘瑶秦志光其他发明人请求不公开姓名
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap