This year’s Baggett Lectures will present an approach to unifying discrete symbolic and continuous neural computation: Gradient Symbolic Computation (GSC). In this second of three lectures in the Baggett Lecture series, use of gradient symbol structures in theories of grammatical competence will be illustrated by partially-present constituents in base positions of syntactic wh-movement, partially-present [voice] features in final consonants in certain final-devoicing languages, and, most extensively, partially-present consonants in underlying forms of French words participating in liaison — consonants which disappear in contexts where fully-present consonants remain. The liaison case illustrates how gradient versions of multiple distinct structures posited by competing theories can be blended to form an account that covers a range of data that no single structure can explain.