Evidence map›Paper›PMID 42225712›Full record

ArticleScientific data2026

A dataset of geographic entities and relationships from Song Dynasty texts on Lin'an.

Chi Zhang, Fengchen Zhong, Zuohui Chen, Wei Wu, Debao Pan

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PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Chi ZhangInstitute of Southern Song Dynasty Capital, Zhejiang University of Technology, Hangzhou, China.
Fengchen ZhongCollege of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China.
Zuohui ChenCollege of Geoinformatics (College of Spatio-temporal Intelligence Engineering), Zhejiang University of Technology, Hangzhou, China. czuohui@zjut.edu.cn.
Wei WuCollege of Geoinformatics (College of Spatio-temporal Intelligence Engineering), Zhejiang University of Technology, Hangzhou, China.
Debao PanInstitute of Southern Song Dynasty Capital, Zhejiang University of Technology, Hangzhou, China.

Funding

Fundamental Research Funds for the Provincial Universities of Zhejiang GB202502013Pioneering and Leading Project of Zhejiang Province 2025C02042
6 · The paper itself

Abstract

The automatic extraction of geographical entities and spatial relationships from historical texts is a fundamental task for Named Entity Recognition (NER) and relation extraction (RE), with important implications for historical geography and digital humanities. Classical Chinese documents describing ancient cities pose particular challenges due to archaic language, implicit spatial expressions, and complex entity hierarchies. In this study, we present a manually annotated dataset designed for joint geographical entity and spatial relationship extraction from texts related to Lin'an, the capital of the Southern Song Dynasty. The dataset consists of 18 in-domain and 1 out-of-distribution historical documents comprising approximately one million Chinese characters, annotated with 24 categories of geographical entities and 34 types of spatial relationships. This dataset provides a valuable resource for advancing NER and spatial relation extraction in historical texts and supports future research in historical Geographic Information Systems (GIS), cultural geography, and digital heritage reconstruction.

Identifiers

PMID42225712
PMCPMC13522433

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