Verb roots encode outcomes: argument structure and lexical semantics of reversal and restitution

This paper explores the distribution and semantics of the reversative affix un- and the restitutive affix re-, and overall makes a new proposal about the lexical semantics of verbs. I argue that these affixes tell a story of derivational morphology that is based not on categorization of verbs into neat aspectual and decompositional classes, but on the result of the verb’s action on the object and whether or not such a result state permits reversal and restitution. The argument structure of these affixes shows us that morphology interacts with semantics in a true compositional sense, whereby the affectedness of the object is a crucial factor in determining compatibility and composition. I propose an approach to verb meaning that encodes this important information as outcomes: the lifespan properties of the object after the action occurs on it. I propose, formulating the Verb-Root-Outcomes framework, that all verb roots come equipped with sets of outcomes. A wide array of verbs that have been classified as ‘change-of-state’ are shown to have different sub-classes based on the shape of the outcome set, and this also allows a formal definition of what ‘potential’ change could mean. The affixes un- and re- are modeled as result-state modifiers, which are sensitive to the outcomes of the action of the verb stem they attach to, and only attach when their presuppositions about the state of the object are met. Apart from directly comparing reversal and restitution with the same formal notion of equivalence, this approach also allows a transparent representation of event decomposition, whereby change in the object is able to be tracked at a granular level and its importance in determining the success of morphological derivations highlighted. This theory argues for compositional semantic interpretation at a sub-lexical level, while also showing how sentential and pragmatic factors affect verb meaning and derivational affixation .