Computing Detailed Colexifications with Missing Data Information from the CLICS⁴ Collection

Abstract

CLICS⁴ offers a refined structural representation of cross-linguistic colexification patterns but retains an implicit representation of missing data. This obscures whether the lack of a colexification in a language for paired concepts is due to its true absence in the language, or due to missing data on the concept or word form level. We introduce a straightforward workflow that can be applied to individual datasets from CLICS⁴ to identify cases of colexification via a three-way attestation scheme. Our approach captures the presence or absence of a colexification in CLICS⁴, but it also explicitly encodes the presence or absence of data at the level of the original questionnaire, or the individual language, elicited with the help of the questionnaire.