Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Entity relationship recognition method and apparatus

An entity relationship and identification method technology, applied in the field of information processing, can solve problems such as no entity relationship identification, inability to timely and effectively exclude wrong relationship patterns, error expansion, etc., to achieve flexible and extensible rule construction, multi-entity relationship The effect of extraction coverage and accurate rule construction

Inactive Publication Date: 2016-09-14
LETV HLDG BEIJING CO LTD +1
View PDF4 Cites 60 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Self-expanding technology first constructs entity-relationship schemas based on unstructured text data, and then uses these schemas to extract relationships from document collections. These new extracted relationships are used to generalize the original schema, and then a new round of extraction is performed. This cycle operates until the extracted relationship meets our requirements. Although this method has bootstrap learning ability, it cannot timely and effectively eliminate the wrong relationship patterns generated during the learning process, and if the wrong relationship patterns cannot be detected If it is discharged in time, it may introduce more wrong relations, and after further use, it will lead to the expansion of mistakes
Moreover, there is no method that combines syntax analysis and Bootstrapping technology to realize entity relationship recognition

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
  • Entity relationship recognition method and apparatus
  • Entity relationship recognition method and apparatus
  • Entity relationship recognition method and apparatus

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0081] The present application will be described in further detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the following exemplary embodiments and descriptions are only used to explain the present invention, not as a limitation to the present invention, and, in the case of no conflict, the embodiments in the application and the features in the embodiments can be combined with each other .

[0082] The present invention provides a method and device for entity relationship recognition. The method is a recognition method based on automatic rule discovery, and a rule base is automatically generated from unmarked text data based on grammatical analysis and a bootstrapping strategy.

[0083] The basic principle of the entity relationship recognition method and device of the present invention is: based on a small number of calibrated high-quality relationship seed sets, using dependency grammar to identify the backbon...

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 present invention relates to an entity relationship recognition method and apparatus. The method comprises obtaining a statement sequence from a target text in a corpus, and performing named entity recognition and dependency grammar marker on the statement sequence to obtain a marked text sentence; matching and retrieving the marked text sentence on basis of an entity relationship seed to obtain a training example; replacing the entity relationship seed word in the training example with predetermined identification, processing the training example after replacement combined with the named entity recognition and the dependency grammar marker, and generating a candidate rule; fuzzifying the candidate rule to obtain fuzzy rules; determining whether the fuzzy rules comprise a new rule; and retrieving the corpus according to the fuzzy rules to obtain a seed set when the fuzzy rules comprise the new rule, and using the obtained seed set as an entity relationship recognition result. Manual participation can be effectively reduced, dependence on the calibrated corpus is reduced, a new entity relationship can be found timely, and the entity relationship recognition method and apparatus are self-adaptive to entity relationship mining in different fields.

Description

technical field [0001] The present invention relates to the technical field of information processing, in particular to an entity relationship recognition method and device based on grammatical analysis and self-expansion. Background technique [0002] Information extraction (Information extraction, abbreviated as IE) technology can help people quickly locate the information they really need in massive information. Information extraction is an unstructured natural language document as input to generate a fixed format and unambiguous format. data process. Information extraction is a research hotspot in natural language processing. There are two important directions in the information extraction system, one is to extract entities from the text, and the other is to determine the relationship between the texts. [0003] The main task of Named Entity Recognition (NER for short) is to identify and classify proper names such as names of people and places and meaningful phrases su...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06F17/27
CPCG06F16/288G06F16/367G06F40/253G06F40/295
Inventor 祁立
Owner LETV HLDG BEIJING CO LTD
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
Eureka Blog
Learn More
PatSnap group products