Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Semantic entity relation extraction method and device, and electronic equipment

An entity relationship and relationship technology, applied in semantic analysis, digital data processing, natural language data processing, etc., can solve the problems of low accuracy rate, incomplete definition, and complex rules of entity relationship, so as to simplify entity relationship extraction and improve utilization. rate, the effect of improving the accuracy

Active Publication Date: 2018-11-23
广东蔚海数问大数据科技有限公司
View PDF4 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, the existing technology relies on paradigm matching for the extraction of parallel relationships, which may lead to extraction omissions due to complex rules and incomplete definitions, resulting in inaccurate extraction of entity relationships. Low rate of technical issues

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
  • Semantic entity relation extraction method and device, and electronic equipment
  • Semantic entity relation extraction method and device, and electronic equipment
  • Semantic entity relation extraction method and device, and electronic equipment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0046] The embodiment of the present invention provides a semantic entity relationship extraction method, which can be used for knowledge map construction and further intelligent search, question answering system, etc.

[0047] Such as figure 1 As shown, the semantic entity relationship extraction method includes the following steps:

[0048] S11: Identify each word node of the input text.

[0049] Each word in the sentence is considered as a node, and the input text is recognized and divided into several word nodes.

[0050]S12: Build the dependency feature of each word node.

[0051] Build a dependency dictionary based on each word and sentence, and the dependency features include the dependency path of candidate nodes and the dependency path dictionary of child nodes. Among them, the first part of the dependency path of the dependency feature is the dependency path from the candidate node to the child node; the second part of the child node dependency feature path dictio...

Embodiment 2

[0085] An embodiment of the present invention provides a semantic entity relationship extraction device, such as figure 2 As shown, the semantic entity relationship extraction device includes: an identification module 21, a construction module 22, an extraction module 23, and a preprocessing module 24 (not shown in the figure).

[0086] Wherein, identification module 21 is used to identify each word node of the input text; Construction module 22 is used to build the dependency feature of each word node; Extraction module 23 is used for when more than two word nodes are parallel relations , by recursively calling the pre-stored semantic rules, extract the relational triples of the candidate nodes; wherein, the pre-stored semantic rules include pre-modified structure rules and verb-related rules, and pre-modified structure classes and verb-related classes can be based on the matching dependency Rules, directly match the input text to extract relational words and entities, and f...

Embodiment 3

[0090] The electronic equipment provided by the embodiment of the present invention, such as image 3As shown, the electronic device includes a processor 30, a memory 31, a bus 32, a communication interface 33, and a computer program stored on the memory 31 and executable on the processor 30. The processor 30, the communication interface 33 and the memory 31 are connected by a bus 32.

[0091] Wherein, the memory 31 may include a high-speed random access memory (RAM, Random Access Memory), and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory. Realize the communication connection between this system network element and at least one other network element through at least one communication interface (can be wired or wireless), can use Internet, wide area network, local network, metropolitan area network etc.

[0092] The bus 32 can be an ISA bus, a PCI bus or an EISA bus, etc. The bus can be divided into address bus, data bus, contr...

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

The invention provides a semantic entity relation extraction method and device, and electronic equipment. The method relates to the fields of artificial intelligence and information extraction technology of natural language processing. The method comprises: identifying each word node of an input text; constructing a dependency characteristic of each word node; and when more than two word nodes arein a coordinating relation, extracting relational triples of candidate nodes by recursively calling pre-stored semantic rules; wherein the pre-stored semantic rules comprise a pre-modification structure rule and a verb-related rule. Compared with the prior art, the method and the device avoid extraction omission due to complicated rules and incomplete definitions by using a recursive method, andcan improve the accuracy of entity relation extraction.

Description

technical field [0001] The present invention relates to the technical field of information extraction of artificial intelligence and natural language processing, in particular to a semantic entity relationship extraction method, device and electronic equipment. Background technique [0002] Information extraction technology can output the unstructured information contained in a large amount of text in a structured or semi-structured form, quickly obtain the information that users care about, and is widely used in knowledge graphs, intelligent search engines, automatic question answering systems, text mining, and machine learning. Translation and many other fields of artificial intelligence. [0003] At present, the traditional supervised and non-open entity relationship extraction method requires a large-scale manually labeled corpus for model training, can only extract predefined relationship types, and is based on a specific field, with poor general applicability. The exi...

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
CPCG06F40/242G06F40/279G06F40/211G06F40/30
Inventor 赵淦森梁昕列海权徐岗赵淑娴纪求华林成创李胜龙唐境灿蔡斯凯李振宇黄伟雄曲成
Owner 广东蔚海数问大数据科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com