The entropy of morphological systems in natural languages is modulated by functional and semantic properties


PsyArXiv Preprints


May, 2021


Francesca Franzon (SISSA) and Chiara Zanini (UZH)

Experimental research has acknowledged the role of
morphological cues of gender and number in prediction, however it is not
clear whether the distribution of words in languages are structured to
systematically exploit them. In a study on Italian, we measured the
distributions of the nominal lexicon across the morphological features,
and found that they are optimized to sustain discrimination and
prediction processes. Though, in a subset of the lexicon denoting
animate referents, the semantic interpretability of the features
significantly alters the distribution, dropping the overall system’s
entropy. We discussed these results in the light of current accounts on
natural language efficiency.