数字人文视域下中国行政区划地名演化知识库构建及分析研究

Constructing Knowledge Base for Chinese Geographical Name

【目的】利用关联数据技术对地名沿革的演变过程进行研究,更好地发挥地名的文化传承作用。【方法】构建中国地名演化知识库CGNE_Onto,制定演变类型强弱标志词识别历史沿革数据中的演变类型句,再利用BERT-BiLSTM-CRF深度学习模型识别演变类型句中的时间和地名实体,将识别出的时间和地名实体作为本体中的类构建本体知识库,同时从直接路径关系和间接路径关系角度对构建好的行政区划地名演化本体知识库进行可视化展示。并对各朝代不同演变类型的数量以及形成原因进行统计分析。【结果】实验结果表明,所提模型能够多角度、直观地展示地名演变情况,为地名数据的分析挖掘提供了一种新的思路。【局限】数据集规模较小,造成演变特征词也有一定的局限。【结论】构建的地名演化知识库能够直观、清晰地展现地名从古至今的演变情况,以及各朝代演变类型的情况。

[Objective]This paper uses linked data technology to study the evolution of geographical names in China,aiming to more effectively conduct digital humanity research.[Methods]First,we constructed the knowledge base CGNE_Onto for the evolution of Chinese geographical names.Then,we formulated the strong and weak marker words to identify evolution type sentences from the historical data.Third,we utilized the BERTBiLSTM-CRF model to identify the time and place name entities from the evolution type sentences.Fourth,we used the newly generated entities as classes to build the ontology knowledge base,which was visualized from the perspective of direct and indirect path relationship.Finally,we analyzed the numbers and reasons of different evolution types in each dynasty.[Results]The proposed model intuitively demonstrated the evolution of geographical names,and provided some new directions for the analysis of geographical names data.[Limitations]The experimental data set needs to be expanded to improve the quality of evolution feature words.[Conclusions]The knowledge base for place names clearly shows their historical evolutions,as well as the evolution types in different dynasties.