Noam Chomsky and other linguists and psychologists have suggested that human linguistic behavior is somehow governed by a mental representation of a transformational grammar. Challenges to this controversial claim have often been met by invoking an explicitly computational perspective: It makes perfect sense to suppose that a grammar could be represented in the memory of a computational device and that this grammar could govern the device's use of a language. This paper urges, however, that the claim that humans are such (...) a device is unsupported and that it seems unlikely that linguists and psychologists really want to claim any such thing. Evidence for the linguists' original claim is drawn from three main sources: the explanation of language comprehension and other linguistic abilities; evidence for formal properties of the rules of the grammar; and the explanation of language acquisition. It is argued in this paper that none of these sources provides support for the view that the grammar governs language processing in something like the way a program governs the operation of a programmed machine. The computational approach, on the contrary, suggests ways in which linguistic abilities can be explained without the attribution of any explicit representation of rules governing linguistic behavior. (shrink)

This paper gives a simple method for providing categorial brands of feature-based unification grammars with a model-theoretic semantics. The key idea is to apply the paradigm of fibred semantics (or layered logics, see Gabbay (1990)) in order to combine the two components of a feature-based grammar logic. We demonstrate the method for the augmentation of Lambek categorial grammar with Kasper/Rounds-style feature logic. These are combined by replacing (or annotating) atomic formulas of the first logic, i.e. the basic syntactic types, by (...) formulas of the second. Modelling such a combined logic is less trivial than one might expect. The direct application of the fibred semantics method where a combined atomic formula like np (num: sg & pers: 3rd) denotes those strings which have the indicated property and the categorial operators denote the usual left- and right-residuals of these string sets, does not match the intuitive, unification-based proof theory. Unification implements a global bookkeeping with respect to a proof whereas the direct fibring method restricts its view to the atoms of the grammar logic. The solution is to interpret the (embedded) feature terms as global feature constraints while maintaining the same kind of fibred structures. For this adjusted semantics, the anticipated proof system is sound and complete. (shrink)

Children learn their native language by exposure to their linguistic and communicative environment, but apparently without requiring that their mistakes be corrected. Such learning from “positive evidence” has been viewed as raising “logical” problems for language acquisition. In particular, without correction, how is the child to recover from conjecturing an over-general grammar, which will be consistent with any sentence that the child hears? There have been many proposals concerning how this “logical problem” can be dissolved. In this study, we review (...) recent formal results showing that the learner has sufficient data to learn successfully from positive evidence, if it favors the simplest encoding of the linguistic input. Results include the learnability of linguistic prediction, grammaticality judgments, language production, and form-meaning mappings. The simplicity approach can also be “scaled down” to analyze the learnability of specific linguistic constructions, and it is amenable to empirical testing as a framework for describing human language acquisition. (shrink)

Parsing according to the principles of modern linguistic theory is only now becoming a computationally interesting task. We contribute to these developments by illustrating how the account of movement introduced by Chomsky inBarriers can be incorporated into a Static Discontinuity Grammar (SDG). We are concerned with A''-movement as reflected inwh movement of arguments and adjuncts. The resulting SDG can be processed by an SDG parser to recover the thematic information and constitutency structure associated with a natural language sentence.

In this article, we first present the platform and the Dislog language, designed for discourse analysis with a logic and linguistic perspective. The platform has now reached a certain level of maturity which allows the recognition of a large diversity of discourse structures including general-purpose rhetorical structures as well as domain-specific discourse structures. The Dislog language is based on linguistic considerations and includes knowledge access and inference capabilities. Functionalities of the language are presented together with a method for writing discourse (...) analysis rules. Efficiency and portability of the system over domains and languages are investigated to conclude this first part. In a second part, we analyse the different types of arguments found in several document genres, most notably: procedures, didactic texts and requirements. Arguments form a large class of discourse relations. A generic and frequently encountered form emerges from our analysis: ?reasons for conclusion? which constitutes a homogeneous family of arguments from a language, functional and conceptual point of view. This family can be viewed as a kind of proto-argument. We then elaborate its linguistic structure and show how it is implemented in . We then investigate the cooperation between explanation and arguments, in particular in didactic texts where they are particularly rich and elaborated. This article ends with a prospective section that develops current and potential uses of this work and how it can be extended to the recognition of other forms of arguments. (shrink)