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Most research on mental lexical representations (lemmas) assumes they are discrete and correspond in number to a word's number of distinct meanings. Thus, homophones ( bat ), whose meanings are unrelated, have separate lemmas for each meaning (one for baseball bat , another for flying bat ), whereas polysemes ( paper ), whose senses are related, have shared lemmas (the same lemma for printer paper and term paper ). However, most aspects of cognition are thought to be graded, not discrete; could lemmas be graded too? We conducted a preregistered picture-word interference study with pictures of words whose meanings ranged from unrelated (homophones) to very related (regular polysemes). Whereas semantic competitors to picture names slow picture naming, semantic competitors to non-depicted meanings of homophones facilitate naming, suggesting distinct lemmas for homophones' meanings. We predicted that competitors to non-depicted senses of polysemes would slow naming, as polysemes' depicted and non-depicted senses presumably share a lemma. Crucially, we aimed to examine the transition from facilitation to inhibition: two groupings (where competitors to non-depicted senses led to facilitation for words with two lemmas but inhibition for words with one lemma) would imply that lemmas are indeed discrete. But a transition that varies continuously by sense relatedness would imply that lemmas are graded. Unexpectedly, competitors to non-depicted senses of both homophones and polysemes facilitated naming. Although these results do not indicate whether lemmas are graded or discrete, they do inform a long-standing question on the nature of polysemes, supporting a multiple-lemma (vs. core-lemma) account., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

An important feature of language production is the flexibility of lexical selection; producers could refer to an animal as chimpanzee, chimp, ape, she, and so on. Thus, a key question for psycholinguistic research is how and why producers make the lexical selections that they do. Information theoretic approaches have argued that producers regulate the uncertainty of the utterance for comprehenders, for example using longer words like chimpanzee if their messages are likely to be misunderstood, and shorter ones like chimp when the message is easy to understand. In this work, we test for the relative contributions of the information theoretic approach and an approach more aligned with psycholinguistic models of language production. We examine the effect on lexical selection of whole utterance-level factors that we take as a proxy for register or style in message-driven production accounts. Using a modern machine learning-oriented approach, we show that for both naturalistic stimuli and real-world corpora, producers prefer words to be longer in systematically different contexts, independent of the specific message they are trying to convey. We do not find evidence for regulation of uncertainty, as in information theoretic approaches. We offer suggestions for modification of the standard psycholinguistic production approach that emphasizes the need for the field to specify how message formulation influences lexical choice in multiword utterances., (Copyright © 2022 Elsevier B.V. All rights reserved.)