Constraint-Based Parsing with Distributed Representations

Abstract

The idea that optimization plays a key role in linguistic cognition is supported by an increasingly large body of research. Building on this research, we describe a new approach to parsing distributed representations via optimization over a set of soft constraints on the wellformedness of parse trees. This work extends previous research involving the use of constraint-based or ``harmonic''' grammars by suggesting how parsing can be accomplished using fully distributed representations that preserve their dimensionality with arbitrary increases in structural complexity. We demonstrate that this method can be used to correctly evaluate the wellformedness of linguistic structures generated by a simple context-free grammar, and discuss a number of extensions concerning the neural implementation of the method and its application to complex parsing tasks.


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