In this article we show how Optimality Theory yields a highly general Constraint Demotion principle for grammar learning. The resulting learning procedure specifically exploits the grammatical structure of Optimality Theory, independent of the content of substantive constraints defining any given grammatical module. We decompose the learning problem and present formal results for a central subproblem, deducing the constraint ranking particular to a target language, given structural descriptions of positive examples. The structure imposed on the space of possible grammars by Optimality Theory allows efficient convergence to a correct grammar. We discuss implications for learning from overt data only, as well as other learning issues. We argue that Optimality Theory promotes confluence of the demands of more effective learnability and deeper linguistic explanation.

Abstract not found

Abstract not found

This article describes an approach to connectionist language research which relies on the development of grammar formalisms rather than computer models. From formulations of the fundamental theoretical commitments of connectionism and of generative grammar, it is argued that these two paradigms are mutually compatible. Integrating the basic assumptions of the paradigms results in formal theories of grammar that centrally incorporate a certain degree of connectionist computation. Two such grammar formalisms --- Harmonic Grammar (Legendre, Miyata and Smolensky, 1990ab) and Optimality Theory (Prince and Smolensky, 1991, 1993) --- are briefly introduced to illustrate grammar-based approaches to connectionist language research. The strengths and weaknesses of grammar-based research and more traditional model-based research are argued to be complementary, suggesting a significant role for both strategies in the spectrum of connectionist language research. This article is addressed to basic ...

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

This paper addresses the application of Optimality Theory (OT) in syntax from a computational point of view. The denition of a processing model for OT syntax presupposes a formalization of the notions involved. Here, the work on an OT account based on Lexical Functional Grammar (LFG) can be used as a basis. In order to guarantee that the processing tasks of generation and parsing with an OT grammar are decidable and computationally tractable, certain restrictions have to be imposed on the formalism. The goal of a computational OT approach is to arrive at a sufficiently restricted formalism that is nevertheless expressive enough to capture the intuitions behind the linguistic OT accounts.

Abstract not found

this paper is twofold. In section 2, I will show that the two constructions exhibit radically dierent properties. In section 3, I will argue that a unied analysis is possible despite these dierences if we assume that shape conservation (Williams (1999)) can be a trigger for movement, in addition to feature checking (Chomsky (1995)). In particular, we will see that whereas primary remnant movement is featuredriven, secondary remnant movement is a repair strategy that is triggered by shape conservation. This latter idea will be implemented in a restrictive model of optimality theory (\local optimization"), for which I will present empirical support.

Abstract not found

num sg neg + inv + 3 7 7 7 5 1 The square brackets in (2) employ attribute-value notation, in which +feature is rendered [feature +] (Johnson, 1988). 1 A similar approach can be adopted in a transformational framework which allows post-movement lexical feature checking, as does the Minimalist Program (MP, Chomsky, 1995). The features of aren't 2 in (2) could be checked against derived positions; the feature Inverted being a special feature which must be checked in C (the inverted position). Yet such language-particular lexical feature specications, whether they are implemented in frameworks with or without movement, are unsatisfying because they fail to relate the specied forms to the rest of the syntactic system. Why, for example, does aren't appear in the inverted position in (1) rather than isn't? Why does a movement paradox o