Solving the elusiveness of word meanings: two arguments for a continuous meaning space for language - Piñango, Maria M. (Frontiers in Artificial Intelligence, 2023)
I explore the hypothesis that the experience of meaning discreteness when we think about the “meaning” of a word is the result of contextual constraints: Context acts as a constraint on meaning, making salient a specific situation-episode within a conceptual space associated with a pronunciation. This salience is what we experience as discreteness. This raises the question of what is context, what are the mechanisms of constraint that it imposes and what is the nature of the conceptual space with which pronunciations associate themselves. I answer these questions by proposing a system for word meaning that is built not of discrete entities, as it is commonly assumed, but of an algebraic system supported by a continuous space; constrained by two fundamental parameters: control-asymmetry and connectedness. I motivate this model by meeting two challenges to word meaning discreteness (1) cases where the same pronunciation is associated with multiple senses that are nonetheless interdependent e.g., English ‘smoke’, and (2) cases where the same pronunciation is associated with a family of meanings, minimally distinct from each other so as to appear as organized under a “cline” e.g., English ‘have’. These cases are not marginal - they are ubiquitous in languages across the world. Any model that captures them is accounting for the meaning system for language. At the heart of the argumentation is the demonstration of how the parametrized space naturally organizes these kinds of cases without appeal to further categorization or segmentation of any kind. From this we conclude that discreteness in word meaning is epiphenomenal: it is the experience of salience produced by contextual constraints. And this is possible because by and large every time that we become consciously aware of the conceptual structure associated with a pronunciation i.e., its meaning, we do so under real-time processing conditions biased towards producing a specific interpretation in reference to a specific situation in the world. Still, the system that makes this salience possible is built from a parametrized space within that stores lexico-conceptual representations, generalized algebraic structures that support cognition in the identification, processing and storage of human understanding of the world.