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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: 2021-07-13
TSINGHUA UNIV
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  • Abstract
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  • Claims
  • Application Information

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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Embodiment Construction

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

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

[0049] S1, obtaining the knowledge map to be input;

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

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Abstract

The invention provides a text generation method and system. The text generation method comprises: obtaining a to-be-input knowledge graph; inputting the knowledge graph to be input into a text generation framework, and constructing an alignment relationship model of the knowledge graph and an output text, wherein the text generation framework is obtained based on knowledge graph and text joint representation learning. Through the text generation framework based on knowledge graph and text joint representation learning, the explicit alignment relationship between the input graph and the output text can be constructed while knowledge graph structure information is introduced at a coding end, and the optimal performance of an existing model is achieved.

Description

technical field [0001] The present invention relates to the technical field of natural language, in particular to a text generation method and system. Background technique [0002] The knowledge graph is one of the important carriers used by humans to store knowledge in the information age, which describes the entities in the world and the relationship between entities. The knowledge map 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 corresponding text of 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 graphs to text generation have 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...

Claims

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Application Information

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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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