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GB/T 45949-2025: Specification for semantic structuring annotation of Chinese news
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| GB/T 45949-2025 | English | 749 |
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Specification for semantic structuring annotation of Chinese news
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GB/T 45949-2025
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Basic data
| Standard ID | GB/T 45949-2025 (GB/T45949-2025) |
| Description (Translated English) | Specification for semantic structuring annotation of Chinese news |
| Sector / Industry | National Standard (Recommended) |
| Classification of Chinese Standard | L60 |
| Classification of International Standard | 35.240.30 |
| Word Count Estimation | 37,393 |
| Date of Issue | 2025-06-30 |
| Date of Implementation | 2025-06-30 |
| Issuing agency(ies) | State Administration for Market Regulation, China National Standardization Administration |
GB/T 45949-2025: Specification for semantic structuring annotation of Chinese news
---This is an excerpt. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.), auto-downloaded/delivered in 9 seconds, can be purchased online: https://www.ChineseStandard.net/PDF.aspx/GBT45949-2025
ICS 35.240.30
CCSL60
National Standard of the People's Republic of China
Semantic structured annotation of Chinese news
Released on June 30, 2025
Implementation on June 30, 2025
State Administration for Market Regulation
The National Standardization Administration issued
Table of Contents
Preface III
Introduction IV
1 Scope 1
2 Normative references 1
3 Terms and Definitions 1
4 Overview of News Semantic Structured Annotation 2
4.1 Labeling Process 2
4.2 Annotation Paradigm 3
5 Preprocessing 4
5.1 Setting the annotation object identifier 4
5.2 News Release Metadata Collection 4
6 Keyword annotation 5
6.1 Marking content 5
6.2 Marking Template 5
6.3 Marking method 5
7 Semantic Template Annotation 6
7.1 Marking content 6
7.2 Marking Templates 14
7.3 Marking method 15
8 Semantic Unit Annotation 16
8.1 Marking content 16
8.2 Marking Templates 17
8.3 Marking method 18
Appendix A (Informative) Application Scenario Examples 23
A.1 Structural management of news content 23
A.2 Generating a Knowledge Base of Manuscript Content 23
A.3 Building a high-quality knowledge graph 23
A.4 Low-cost and high-efficiency training of artificial neural network models 23
Appendix B (Informative) Complete Example of News Semantic Structured Annotation 24
B.1 Original 24
B.2 Preprocessing 24
B.3 Keyword Annotation 26
B.4 Semantic Template Annotation 27
B.5 Semantic Unit Annotation 29
Reference 32
Preface
This document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for standardization work Part 1.Structure and drafting rules for standardization documents"
Drafting.
Please note that some of the contents of this document may involve patents. The issuing organization of this document does not assume the responsibility for identifying patents.
This document was proposed and coordinated by the National Technical Committee for Standardization of Chinese News Information (SAC/TC352).
This document was drafted by. Wenling Technology (Beijing) Co., Ltd., Beijing Language and Culture University, Southeast University, Xinhua News Agency, China Internet News
News Center, China Academy of Information and Communications Technology, Zhejiang Daily Newspaper Group, and Baoding Data Bureau (National Data Labeling Base).
The main drafters of this document are. Wang Nan, Rao Gaoqi, Yang Peng, Ding Desheng, Wang Yi, Fu Rong, Wang Guirong, Wang Jianping, Huang Jing, Li Sun, Jia Chengxi,
Zhang Chuang, Li Bing, Yang Dongmei, Zhou Tianwai, and Song Yongsheng.
introduction
With the widespread application of artificial intelligence technology in the news field, establishing standardized Chinese news data processing standards has become an important part of industry development.
This document is formulated to build a unified Chinese news semantic annotation system, through a standardized data processing process to achieve
The following two major goals. one is to provide support for the systematic construction of news knowledge base and knowledge graph; the other is to improve the training of artificial neural network models
Improve data quality and efficiency, and promote the intelligent transformation of the news industry.
Semantic structured annotation of Chinese news
1 Scope
This document specifies the preprocessing, keyword annotation, semantic template annotation and semantic unit annotation of Chinese news semantic structured annotation.
method.
This document is suitable for news content providers, media applications and research institutions to manually annotate news articles, and can also be used for machine automation.
Annotation.
This document is not intended for semantically structured annotation across manuscripts.
2 Normative references
The contents of the following documents constitute the essential clauses of this document through normative references in this document.
For referenced documents without a date, only the version corresponding to that date applies to this document; for referenced documents without a date, the latest version (including all amendments) applies to
This document.
GB/T 20092.2-2022 Chinese News Information Content Part 2.News Metadata
GB/T 20093-2022 Classification and Code of Chinese News Information
3 Terms and Definitions
The following terms and definitions apply to this document.
3.1
keyword
Words that represent specific semantics in news articles.
Note. “Specific semantics” refers to the content of the news article that the annotator considers important, including the article’s theme, important people, important events, and important common sense.
3.2
semantic unit
The basic unit that expresses complete semantics in news releases.
Note. Semantic units are mainly divided into entities, things, events and other types, and are the basis for complex semantic structures including knowledge graphs.
3.3
Describes or defines the characteristic quantity of a semantic unit.
NOTE. Semantic unit parameters include attributes, properties, aspects, capabilities (purposes), categories, limitations and states.
3.4
stateofsemanticunit
The set of values of semantic unit parameters in a specific time and space.
Note. The state of a semantic unit is used to describe the dynamic nature of the development and change of things. When marking, it is marked as a parameter of the semantic unit.
3.5
semantictemplate
A fixed structure that expresses semantics.
Note. It consists of core elements, limiting elements and their relationships.
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