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Entity relationship extraction method fusing trigger word recognition features

A technology of entity relationship and feature recognition, applied in character and pattern recognition, special data processing applications, instruments, etc., can solve problems such as noise

Active Publication Date: 2020-07-17
BEIJING INSTITUTE OF TECHNOLOGYGY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to solve the noise problem caused by the existing entity relationship extraction method that treats all words in the sentence equally, and proposes an entity relationship extraction method that integrates trigger word recognition features

Method used

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  • Entity relationship extraction method fusing trigger word recognition features
  • Entity relationship extraction method fusing trigger word recognition features
  • Entity relationship extraction method fusing trigger word recognition features

Examples

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Embodiment 1

[0087] This embodiment illustrates the specific implementation of a method for extracting entity relationships that integrates trigger word recognition features according to the present invention.

[0088] figure 1 Shown is the flowchart of the method.

[0089] Step 1. Design a model to identify trigger words in sentences;

[0090] Step 1.1 marks the trigger words for the sentences in the data set, and for sentences with trigger words, for example, "In the Institute of Automation, Chinese Academy of Sciences, there is a Sino-French Joint Laboratory of Automation and Applied Mathematics"; the two entities of this sentence are "China Academy of Sciences Institute of Automation" and "Sino-French Joint Laboratory of Automation and Applied Mathematics", the entity relationship expressed is "ART / User-Owner-Inventor-Manufacturer". The word "有" in the sentence can directly express the entity relationship. Use braces to mark this word as a trigger word, which is used to reco...

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Abstract

The invention relates to an entity relationship extraction method fusing trigger word recognition features, and belongs to the technical field of information extraction in natural language processing.The method comprises the following steps: marking sentences in a data set with trigger words; utilizing trigger words in sentences, two entities and sentence types calculated according to relative positions of the two entities to calculate label vectors, and then calculating relative entropy expressed by the label vectors and sentence features captured by an attention mechanism in the model; designing a target function for entity relationship extraction; and optimizing the relative entropy and the objective function of entity relationship extraction to train an entity relationship extractionmodel. Not only is the defect that all words in sentences seen in an existing entity relationship extraction method overcome, but also theentity relationship extraction model can be helped to extractfeatures which are more useful for entity relationship classification; according to the entity relationship extraction method, the F1 score of a standard Chinese relationship extraction data set ACE2005 is 2.5% higher than that of an existing best entity relationship extraction method.

Description

technical field [0001] The invention relates to a method for extracting entity relations by integrating trigger word recognition features, and belongs to the technical field of information extraction in natural language processing. Background technique [0002] The task of entity relationship extraction is to give a sentence labeled with two entities and return the semantic relationship between the two entities. For example, "Yao Ming, under the influence of his father Yao Zhiyuan, also loves basketball very much", the two entities in the sentence are "Yao Ming" and "Yao Zhiyuan", and the relationship between the two entities is "father and son". [0003] Entity relationship extraction is an important supporting technology for information systems such as information retrieval and question answering systems. Entity relationship extraction transforms the output of information system from coarse-grained document level to fine-grained entity level. For example, in traditional ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F40/295G06F40/284G06F16/35G06K9/62
CPCG06F16/35G06F18/253
Inventor 辛欣王艳
Owner BEIJING INSTITUTE OF TECHNOLOGYGY