Edward P. Stabler
While research in the ‘principles and parameters’ tradition can be regarded as attributing as much as possible to universal grammar (UG) in order to understand how language acquisition is possible, Chomsky characterizes the ‘minimalist program’ as an effort to attribute as little as possible to UG while still accounting for the apparent diversity of human languages. These two research strategies aim to be compatible, and ultimately should converge. Several of Chomsky's own early contributions to the minimalist program have been fundamental and simple enough to allow easy mathematical and computational study. Among these are (i) the characterization of ‘bare phrase structure’; and (ii) the definition of a structure building operation Merge which applies freely to lexical material, with constraints that ‘filter’ the results only at the phonetic form and logical form interfaces. The first studies inspired by (i) and (ii) are ‘stripped down’ to such a degree that they may seem unrelated to minimalist proposals, but this article shows how some easy steps begin to bridge the gap. It briefly surveys some proposals about (iii) syntactic features that license structure building; (iv) ‘locality’, the domain over which structure building functions operate,; (v) ‘linearization’, determining the order of pronounced forms; and (vi) the proposal that Merge involves copying.
This chapter aims to introduce readers not familiar with computational modelling to some approaches and issues in the formal study of learnability, and the relevance of this field to theoretical linguistics and inflectional morphology in particular. After a general overview, the chapter highlights some of the obstacles in learning inflection. Inflection, considered separately from other components of language, is relatively restricted in its expressive power, which should make it easier to learn than syntax. However, inflectional systems are full of irregularities and mismatches between different levels of structure, and such irregularities make learning difficult. Overall, it is concluded that linguistically interesting proposals for machine learning of inflection should provide explanations for the nature and extent of irregularities and for the specific patterns of language acquisition and language change.
Ronald M. Kaplan
This chapter introduces some of the phenomena that theories of natural-language syntax aim to account for. It briefly discusses the correspondence between the sentences of a language and the semantic predicate-argument relations that they express, indicating how that correspondence is encoded in terms of word order, phrase structure, agreement, and valence. It surveys some of the grammatical notations, syntactic representations, and theoretical approaches that have figured prominently in linguistic research and that have particularly influenced the development of natural-language processing algorithms and implementations.