Despite the inherently fuzzy nature of reconstructions in historical
linguistics, most scholars do not represent their uncertainty when proposing
proto-forms. With the increasing success of recently proposed approaches to
automating certain aspects of the traditional comparative method, the formal
representation of proto-forms has also improved. This formalization makes it
possible to address both the representation and the computation of uncertainty.
Building on recent advances in supervised phonological reconstruction, during
which an algorithm learns how to reconstruct words in a given proto-language
relying on previously annotated data, and inspired by improved methods for
automated word prediction from cognate sets, we present a new framework that
allows for the representation of uncertainty in linguistic reconstruction and
also includes a workflow for the computation of fuzzy reconstructions from
linguistic data.

通过最近提出的自动化传统比较方法某些方面的方法的成功，以及灵感来源于改进的同源词集自动预测方法，我们提出了一个新的框架，允许在语言重建中表示不确定性，并包含从语言数据计算模糊重建的工作流程。