用AI首次系统识别圣经中的回环修辞，精准度超80%。
Computational Discovery of Chiasmus in Ancient Religious Text
- 通过神经嵌入捕捉词汇与语义模式，多粒度检测回环结构。
- 句级检测精度达0.80，半句级达0.60，专家验证一致性高。
- 适合文本分析、数字人文及宗教文献研究者使用。
回环（Chiasmus）是《圣经》中存在争议的文学手法，长期吸引神秘主义者并引发学术争论。本文首次提出系统性计算方法，用于检测《圣经》段落中的回环结构。该方法利用神经嵌入捕捉与回环相关的词汇和语义模式，在半节经文与整节经文两个粒度层级上应用。我们还邀请专家对部分检测结果进行人工复核。尽管计算效率高，模型在句级达到0.80的precision@k，在半句级为0.60，且具备高专家一致性。此外，我们提供了检测到的回环分布的定性分析，并展示若干典型实例，凸显方法的有效性。
原文摘要 · Abstract (English)
Chiasmus, a debated literary device in Biblical texts, has captivated mystics while sparking ongoing scholarly discussion. In this paper, we introduce the first computational approach to systematically detect chiasmus within Biblical passages. Our method leverages neural embeddings to capture lexical and semantic patterns associated with chiasmus, applied at multiple levels of textual granularity (half-verses, verses). We also involve expert annotators to review a subset of the detected patterns. Despite its computational efficiency, our method achieves robust results, with high inter-annotator agreement and system precision@k of 0.80 at the verse level and 0.60 at the half-verse level. We further provide a qualitative analysis of the distribution of detected chiasmi, along with selected examples that highlight the effectiveness of our approach.
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