Computing Detailed Colexifications with Missing Data Information from the CLICS⁴ Collection | Computer-Assisted Language Comparison in Practice: Tutorials on Computational Approaches to the History and Diversity of Languages

EvoBib

Vom Winden vor Winden

Mit viel linguistischem Interesse habe ich vor kurzem einen populärwissenschaftlichen Artikel von Schubert (2026) gelesen, der von einer Forschungsgruppe handelt, der es gelungen war, die täglichen Blähungen von Menschen viel genauer als zuvor zu messen (Botasini et al. 2025). Dieser Gruppe war es gelungen, einen spezifischen Unterhoseneinsatz zu konstruieren, welcher sich als smart wearable via […]

Using Correspondence Patterns to Identify Irregular Words in Cognate sets Through Leave-One-Out Validation

Regular sound correspondences constitute the principal evidence in historical language comparison. Despite the heuristic focus on regularity, it is often more an intuitive judgement than a quantified evaluation, and irregularity is more common than expected from the Neogrammarian model. Given the recent progress of computational methods in historical linguistics and the increased availability of standardized lexical data, we are now able to improve our workflows and provide such a quantitative evaluation. Here, we present the balanced average recurrence of correspondence patterns as a new measure of regularity. We also present a new computational method that uses this measure to identify cognate sets that lack regularity with respect to their correspondence patterns. We validate the method through two experiments, using simulated and real data. In the experiments, we employ leave-one-out validation to measure the regularity of cognate sets in which one word form has been replaced by an irregular one, checking how well our method identifies the forms causing the irregularity. Our method achieves an overall accuracy of 85\% with the datasets based on real data. We also show the benefits of working with subsamples of large datasets and how increasing irregularity in the data influences our results. Reflecting on the broader potential of our new regularity measure and the irregular cognate identification method based on it, we conclude that they could play an important role in improving the quality of existing and future datasets in computer-assisted language comparison.

Transparent Application of Text Generation Tools in Scientific Research

In this opinion piece, I share my view on the application of language models and text generation services in scientific research. In my opinion, scientific research that lives up to the promises of open science must provide full documentation of all prompts and exchanges that were used to create a given study. A mere mention […]

Vom Fabulieren und Halluzinieren

In der letzten Zeit wird sehr oft vom Halluzinieren gesprochen. Allerdings nicht in Bezug auf Menschen, die ja auch selten von Halluzinationen heimgesucht werden, als vielmehr in Bezug auf Sprachmodelle, die komische Antworten liefern, die keinen Sinn ergeben oder sich angebliche Fakten zusammenfabulieren, für die es keine Belege gibt. Dass es problematisch ist, dieses nicht […]