List Johann-Mattis
Department of Linguistic and Cultural Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.
Chair of Multilingual Computational Linguistics, University of Passau, Passau, Germany.
Front Psychol. 2023 Jun 16;14:1156540. doi: 10.3389/fpsyg.2023.1156540. eCollection 2023.
The past years have seen a drastic rise in studies devoted to the investigation of colexification patterns in individual languages families in particular and the languages of the world in specific. Specifically computational studies have profited from the fact that colexification as a scientific construct is easy to operationalize, enabling scholars to infer colexification patterns for large collections of cross-linguistic data. Studies devoted to partial colexifications-colexification patterns that do not involve entire words, but rather various parts of words-, however, have been rarely conducted so far. This is not surprising, since partial colexifications are less easy to deal with in computational approaches and may easily suffer from all kinds of noise resulting from false positive matches. In order to address this problem, this study proposes new approaches to the handling of partial colexifications by (1) proposing new models with which partial colexification patterns can be represented, (2) developing new efficient methods and workflows which help to infer various types of partial colexification patterns from multilingual wordlists, and (3) illustrating how inferred patterns of partial colexifications can be computationally analyzed and interactively visualized.
在过去几年中,专门研究特定语系(尤其是个别语系)和世界上各种语言的共词化模式的研究急剧增加。具体而言,计算研究得益于这样一个事实:共词化作为一种科学结构易于操作,使学者们能够推断出大量跨语言数据的共词化模式。然而,迄今为止,针对部分共词化(即不涉及整个单词,而是单词的各个部分的共词化模式)的研究却很少。这并不奇怪,因为部分共词化在计算方法中较难处理,并且可能容易受到由误匹配导致的各种噪声的影响。为了解决这个问题,本研究提出了处理部分共词化的新方法:(1)提出可以表示部分共词化模式的新模型;(2)开发新的高效方法和工作流程,以帮助从多语言词表中推断出各种类型的部分共词化模式;(3)说明如何对推断出的部分共词化模式进行计算分析和交互式可视化。