Recapturing the Flow of Knowledge:Tracing Structured Knowledge Back to Historical Records
Tracing structured historical knowledge back to historical records can enhance the verifiability and reliability of knowledge.In response to the challenges of inadequate knowledge tracing mechanisms in existing knowledge bases of an-cient books and the absence of trigger words in several Archaic Chinese texts,this study introduces a method to trace struc-tured historical knowledge back to historical records.First,a structured historical knowledge tracing framework is pro-posed by leveraging techniques such as co-reference resolution and textual entailment.Subsequently,a dataset is proposed to compare the effectiveness of different pre-trained language models,including BERT,SikuBERT,GPT-3,and GPT-4.This dataset combined with different input strategies on the knowledge tracing effect,is used to structure the historical knowledge tracing model,SHK-Tracer,which was employed to trace the historical subject matter knowledge base(Shiji Mutil-dimensional Knowledge Base,SMKB)to different ancient historical books,with 80.19%precision.We found that the knowledge overlap between Shiji and each historical fragment in historical books,such as Zuozhuan and Guoyu,did not correlate proportionally with the inherent information content of the historical fragment.The results of the study serve the dual purpose of first,aiding scholars and readers in verifying the authenticity of knowledge,by providing cross-refer-ences between different historical sources and identifying the original source;and second,facilitating digital humanities re-search,including historical knowmetrics,relation extraction,and linguistic style calculations of ancient historical records.
NETL
NSTL
万方数据
维普
