Modeling rules and similarity in colexification.

Colexification, or the expression of multiple concepts by the same word, is ubiquitous in language. Colexifications may appear rule-like, as when an artifact is used for an activity (repair the shower/take a shower), or similarity-based (child refers to both “young person” and “descendant”). We investigate whether these two modes of generalization (rules and similarity) reflect how people structure new meanings. We propose computational models based on rules, similarity, and a hybrid of the two, and correlate model predictions to human behavior—in a novel task, participants generalized labels across colexified meanings. We found that a model using similarity correlated much better with human behavior than rules, and that the similarity model was significantly outperformed by a hybrid model of the two mechanisms. However, the difference between similarity and hybrid was modest, suggesting that a framework which combines rules and similarity largely relies on similarity-based generalization to characterize human expectations about colexification.