Abstract Deriving historical dates or datable stratifications for texts in Classical Sanskrit, such as the epics Mahābhārata and Rāmāyaṇa, is a considerable challenge for text-historical research. This paper provides empirical evidence for subtle but noticeable diachronic changes in the fundamental linguistic structures of Classical Sanskrit, and argues that Classical Sanskrit shows enough diachronic variation for dating texts on the basis of linguistic developments. Building on this evidence, it evaluates machine learning algorithms that predict approximate dates of composition for Sanskrit texts. The paper introduces the required background, discusses the relevance of linguistic features for temporal classification, and presents a text-historical evaluation of Book 6 of the Mahābhārata, whose historical stratification is disputed in Indological research.

中文翻译：

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使用语言特征和神经网络约会梵文文本

摘要 为古典梵文文本（例如史诗摩诃婆罗多和罗摩耶）推导历史日期或可数据的分层，是文本历史研究的一个相当大的挑战。本文为古典梵文基本语言结构的微妙但显着的历时变化提供了经验证据，并认为古典梵文在语言发展的基础上对约会文本显示出足够的历时变化。基于此证据，它评估了机器学习算法，这些算法可以预测梵文文本的大致写作日期。该论文介绍了所需的背景，讨论了语言特征与时间分类的相关性，并提出了对《摩诃婆罗多》第六卷的文本历史评价，