This year’s Baggett Lectures will present an approach to unifying discrete symbolic and continuous neural computation: Gradient Symbolic Computation (GSC). In this third lecture in the Baggett Lecture series, Gradient Symbolic Computation process models of incremental (word-by-word) syntactic parsing will be discussed, as well as process models of graded probabilistic biases in language learning and the potential role of such biases in explaining statistical typological universals.