Connectionist sentence processing in perspective

The emphasis in the connectionist sentence-processing literature on distributed representation and emergence of grammar from such systems seems to have prevented connectionists and symbolists alike from recognizing the often close relations between their respective systems. This paper argues that simply recurrent network (SRN) models proposed by Jordan (1990) and Elman (1990) are more directly related to stochastic Part-of-Speech (POS) Taggers than to parsers or grammars as such, while recursive auto-associative memory (RAAM) of the kind pioneered by Pollack and incorporated in many hybrid connectionist parsers since may be useful for grammar induction from a network-based conceptual structure as well as for structure-building. These observations suggest some interesting new directions for connectionist sentence processing research, including more efficient devices for representing finite state machines, and acquisition devices based on a distinctively connectionist grounded conceptual structure.