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A text generation method and system

A text and text sequence technology, applied in the field of text generation methods and systems, can solve problems such as insufficient coding of structural information in knowledge graphs, no explicit modeling graph and text alignment relationship, and achieve optimal performance

Active Publication Date: 2022-08-09
TSINGHUA UNIV
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AI Technical Summary

Problems solved by technology

Nevertheless, pre-trained language models still face two major challenges when applying knowledge graphs to text generation tasks: 1) Insufficient encoding of the structural information of knowledge graphs; 2) There is no explicit alignment relationship between modeling graphs and texts

Method used

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  • A text generation method and system
  • A text generation method and system
  • A text generation method and system

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Embodiment Construction

[0047] In order to make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention. , not all examples. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0048] figure 1 is a schematic flowchart of the text generation method provided by the present invention, such as figure 1 shown, including:

[0049] S1, obtain the knowledge graph to be input;

[0050] S2, the knowledge graph to be input is input into a text generation framework, and an alignment relationship model between the knowledge graph and the output text is constructed; wherein the text generation frame...

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Abstract

The present invention provides a text generation method and system, including: acquiring a knowledge graph to be input; inputting the knowledge graph to be input into a text generation framework, and constructing an alignment relationship model between the knowledge graph and output text; wherein the The text generation framework is based on knowledge graph and text joint representation learning. Through the text generation framework based on knowledge graph and text joint representation learning, the present invention can construct the explicit alignment relationship between the input graph and the output text while introducing the knowledge graph structure information at the coding end, so as to achieve the optimal performance of the existing model.

Description

technical field [0001] The present invention relates to the technical field of natural language, and in particular, to a text generation method and system. Background technique [0002] Knowledge graph is one of the important carriers for human beings to store knowledge in the information age, which describes the relationship between entities and entities in the world. The knowledge graph contains a large amount of structured data, which is often stored in the form of triples. For example, (Beijing, is the capital of ..., China) The text corresponding to this triple is "Beijing is the capital of China". [0003] In practical applications, it is usually necessary to convert knowledge graphs into natural language texts, so knowledge graph-to-text generation has become one of the classic tasks in the field of natural language processing. With the development of large-scale pre-trained language models in recent years, pre-trained language generation models such as GPT, BART, an...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/36G06F40/279G06F40/30G06N3/04G06N3/08
CPCG06F16/367G06F40/30G06F40/279G06N3/04G06N3/08
Inventor 黄民烈柯沛朱小燕
Owner TSINGHUA UNIV
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