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Number in Language  

Paolo Acquaviva

Number is the category through which languages express information about the individuality, numerosity, and part structure of what we speak about. As a linguistic category it has a morphological, a morphosyntactic, and a semantic dimension, which are variously interrelated across language systems. Number marking can apply to a more or less restricted part of the lexicon of a language, being most likely on personal pronouns and human/animate nouns, and least on inanimate nouns. In the core contrast, number allows languages to refer to ‘many’ through the description of ‘one’; the sets referred to consist of tokens of the same type, but also of similar types, or of elements pragmatically associated with one named individual. In other cases, number opposes a reading of ‘one’ to a reading as ‘not one,’ which includes masses; when the ‘one’ reading is morphologically derived from the ‘not one,’ it is called a singulative. It is rare for a language to have no linguistic number at all, since a ‘one–many’ opposition is typically implied at least in pronouns, where the category of person discriminates the speaker as ‘one.’ Beyond pronouns, number is typically a property of nouns and/or determiners, although it can appear on other word classes by agreement. Verbs can also express part-structural properties of events, but this ‘verbal number’ is not isomorphic to nominal number marking. Many languages allow a variable proportion of their nominals to appear in a ‘general’ form, which expresses no number information. The main values of number-marked elements are singular and plural; dual and a much rarer trial also exist. Many languages also distinguish forms interpreted as paucals or as greater plurals, respectively, for small and usually cohesive groups and for generically large ones. A broad range of exponence patterns can express these contrasts, depending on the morphological profile of a language, from word inflections to freestanding or clitic forms; certain choices of classifiers also express readings that can be described as ‘plural,’ at least in certain interpretations. Classifiers can co-occur with other plurality markers, but not when these are obligatory as expressions of an inflectional paradigm, although this is debated, partly because the notion of classifier itself subsumes distinct phenomena. Many languages, especially those with classifiers, encode number not as an inflectional category, but through word-formation operations that express readings associated with plurality, including large size. Current research on number concerns all its morphological, morphosyntactic, and semantic dimensions, in particular the interrelations of them as part of the study of natural language typology and of the formal analysis of nominal phrases. The grammatical and semantic function of number and plurality are particularly prominent in formal semantics and in syntactic theory.

Article

Connectionism in Linguistic Theory  

Xiaowei Zhao

Connectionism is an important theoretical framework for the study of human cognition and behavior. Also known as Parallel Distributed Processing (PDP) or Artificial Neural Networks (ANN), connectionism advocates that learning, representation, and processing of information in mind are parallel, distributed, and interactive in nature. It argues for the emergence of human cognition as the outcome of large networks of interactive processing units operating simultaneously. Inspired by findings from neural science and artificial intelligence, connectionism is a powerful computational tool, and it has had profound impact on many areas of research, including linguistics. Since the beginning of connectionism, many connectionist models have been developed to account for a wide range of important linguistic phenomena observed in monolingual research, such as speech perception, speech production, semantic representation, and early lexical development in children. Recently, the application of connectionism to bilingual research has also gathered momentum. Connectionist models are often precise in the specification of modeling parameters and flexible in the manipulation of relevant variables in the model to address relevant theoretical questions, therefore they can provide significant advantages in testing mechanisms underlying language processes.