Balance of meaning probabilities in processing of Serbian homonymy

Abstract

The research deals with the set of Serbian homonymous nouns (nouns with multiple unrelated meanings) presented in the norming study and in the visual lexical decision task experiment. Native speakers listed the meanings of homonymous words and provided word familiarity and word concreteness ratings. Accordingly, the first database of Serbian homonyms was constructed containing subjective meanings of homonymous nouns along with the estimated meaning probabilities, as well as a number of meanings, redundancy and entropy of the distribution of meaning probabilities, word familiarity and word concreteness. The processing disadvantage of homonymous nouns over unambiguous nouns was replicated in the visual lexical decision task. Additionally, the processing of homonymous nouns was linked with redundancy: the information theory measure of the balance of meaning probabilities. The results revealed that homonyms with higher redundancy of the meaning probability distribution (i.e., unbalanced meaning probabilities) were processed faster. This finding was in accordance with the hypothesis derived from the Semantic Settling Dynamics account of the processing of ambiguous words, according to which the competition among the unrelated meanings derived the processing disadvantage in homonymy. However, the same pattern was not observed for the number of meanings and entropy, inviting for further research of the processing of ambiguous words.