Computing Detailed Colexifications with Missing Data Information from the CLICS⁴ Collection

CLICS⁴ offers a refined structural representation of cross-linguisitic 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 straightforward workflow that can be applied to individual dataset 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.