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Colexification refers to the linguistic phenomenon where a single lexicalform is used to convey multiple meanings. By studying cross-lingualcolexifications, researchers have gained valuable insights into fields such aspsycholinguistics and cognitive sciences [Jackson et al.,2019]. While severalmultilingual colexification datasets exist, there is untapped potential inusing this information to bootstrap datasets across such semantic features. Inthis paper, we aim to demonstrate how colexifications can be leveraged tocreate such cross-lingual datasets. We showcase curation procedures whichresult in a dataset covering 142 languages across 21 language families acrossthe world. The dataset includes ratings of concreteness and affectiveness,mapped with phonemes and phonological features. We further analyze the datasetalong different dimensions to demonstrate potential of the proposed proceduresin facilitating further interdisciplinary research in psychology, cognitivescience, and multilingual natural language processing (NLP). Based on initialinvestigations, we observe that i) colexifications that are closer inconcreteness/affectiveness are more likely to colexify; ii) certaininitial/last phonemes are significantly correlated withconcreteness/affectiveness intra language families, such as /k/ as the initialphoneme in both Turkic and Tai-Kadai correlated with concreteness, and /p/ inDravidian and Sino-Tibetan correlated with Valence; iii) the type-to-tokenratio (TTR) of phonemes are positively correlated with concreteness acrossseveral language families, while the length of phoneme segments are negativelycorrelated with concreteness; iv) certain phonological features are negativelycorrelated with concreteness across languages. The dataset is made publiconline for further research.

Colexifications for Bootstrapping Cross-lingual Datasets: The Case of Phonology, Concreteness, and Affectiveness