The Entropy of Morphological Systems in Natural Languages Is Modulated by Functional and Semantic Properties

Abstract

In most natural languages, grammatical gender and number features encode semantic attributes concerning animacy, sex, and numerosity. Despite the likely advantage of promptly communicating about such salient attributes, inflectional systems rarely display consistently bijective correspondences between the semantic attributes and the grammatical feature values. In a study on Italian, we explored how this apparently noisy encoding depends on a trade-off between the semantic and the functional aspects of grammatical features. Using entropy metrics, we assessed the primarily functional purpose of gender and number features in the lexicon, observing a distribution of nouns that can optimally serve agreement-based parsing and prediction of words in sentences. A novel context entropy measure, introduced in this study to assess meaning specificity, revealed a semantic underspecification in masculine and singular nouns denoting animate referents. We argue that underspecification is the hallmark of the particular type of information compression occurring in inflectional systems. In binary inflectional systems, one value specifically encodes a semantic attribute, while the other value does not encode any semantic information, and surfaces as a default for functional purposes. By providing an information-theoretical account of the role of grammatical features, we set the basis for a scientifically informed pursue of language inclusiveness.