Researchers have developed a new framework to analyze the stylistic features of early Chinese Buddhist translations, aiming to improve attribution accuracy. This framework utilizes linguistic elements such as function characters, sentence structure, and part-of-speech n-grams, as defined by Buddhist philologists. By comparing stylistic profiles of authenticated translations with disputed works, the study identified two texts, T1557 and T0101, as having strong stylistic similarities to the works of An Shigao, with scores of 0.783 and 0.687 respectively. This approach aligns with previous BERT-based findings and allows for transparent inspection of the linguistic features supporting attributions. AI
IMPACT This framework could enhance the accuracy and transparency of textual attribution in historical and linguistic studies.
RANK_REASON The cluster contains a research paper detailing a new methodology for text analysis. [lever_c_demoted from research: ic=1 ai=0.7]
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →