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Ever since Chomsky laid the framework for a mathematically formal theory of syntax, two classes of formal models have held wide appeal. The finite state model offered simplicity. At the opposite extreme numerous very powerful models, most notable transformational grammar, offered generality. As soon as this mathematical framework was laid, devastating arguments were given by Chomsky and others indicating that the finite state model was woefully inadequate for the syntax of natural language. In response, the completely general transformational grammar model was advanced as a suitable vehicle for capturing the description of natural language syntax. While transformational grammar seems likely to be adequate to the task, many researchers have advanced the argument that it is "too adequate. " A now classic result of Peters and Ritchie shows that the model of transformational grammar given in Chomsky's Aspects [IJ is powerful indeed. So powerful as to allow it to describe any recursively enumerable set. In other words it can describe the syntax of any language that is describable by any algorithmic process whatsoever. This situation led many researchers to reasses the claim that natural languages are included in the class of transformational grammar languages. The conclu sion that many reached is that the claim is void of content, since, in their view, it says little more than that natural language syntax is doable algo rithmically and, in the framework of modern linguistics, psychology or neuroscience, that is axiomatic.
This comprehensive reference work provides an overview of the concepts, methodologies, and applications in computational linguistics and natural language processing (NLP). Features contributions by the top researchers in the field, reflecting the work that is driving the discipline forward Includes an introduction to the major theoretical issues in these fields, as well as the central engineering applications that the work has produced Presents the major developments in an accessible way, explaining the close connection between scientific understanding of the computational properties of natural language and the creation of effective language technologies Serves as an invaluable state-of-the-art reference source for computational linguists and software engineers developing NLP applications in industrial research and development labs of software companies
The central task of future-oriented computational linguistics is the development of cognitive machines which humans can freely speak to in their natural language. This will involve the development of a functional theory of language, an objective method of verification, and a wide range of practical applications. Natural communication requires not only verbal processing, but also non-verbal perception and action. Therefore, the content of this book is organized as a theory of language for the construction of talking robots with a focus on the mechanics of natural language communication in both the listener and the speaker.
This book contains original reviews by well-known workers in the field of mathematical linguistics and formal language theory, written in honour of Professor Solomon Marcus on the occasion of his 70th birthday.Some of the papers deal with contextual grammars, a class of generative devices introduced by Marcus, motivated by descriptive linguistics. Others are devoted to grammar systems, a very modern branch of formal language theory. Automata theory and the algebraic approach to computer science are other well-represented areas. While the contributions are mathematically oriented, practical issues such as cryptography, grammatical inference and natural language processing are also discussed.
Quantification is a topic which brings together linguistics, logic, and philosophy. Quantifiers are the essential tools with which, in language or logic, we refer to quantity of things or amount of stuff. In English they include such expressions as no, some, all, both, and many. Peters and Westerstahl present the definitive interdisciplinary exploration of how they work - their syntax, semantics, and inferential role.Quantifiers in Language and Logic is intended for everyone with a scholarly interest in the exact treatment of meaning. It presents a broad view of the semantics and logic of quantifier expressions in natural languages and, to a slightly lesser extent, in logical languages. The authors progress carefully from a fairly elementary level to considerable depth over the course of sixteen chapters; their book will be invaluable to a broad spectrum of readers, from those with a basicknowledge of linguistic semantics and of first-order logic to those with advanced knowledge of semantics, logic, philosophy of language, and knowledge representation in artificial intelligence.
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This book presents a challenge to the widely-held assumption that human languages are both similar and constant in their degree of complexity. For a hundred years or more the universal equality of languages has been a tenet of faith among most anthropologists and linguists. It has been frequently advanced as a corrective to the idea that some languages are at a later stage of evolution than others. It also appears to be an inevitable outcome of one of the central axioms of generative linguistic theory: that the mental architecture of language is fixed and is thus identical in all languages and that whereas genes evolve languages do not. Language Complexity as an Evolving Variable reopens the debate. Geoffrey Sampson's introductory chapter re-examines and clarifies the notion and theoretical importance of complexity in language, linguistics, cognitive science, and evolution. Eighteen distinguished scholars from all over the world then look at evidence gleaned from their own research in order to reconsider whether languages do or do not exhibit the same degrees and kinds of complexity. They examine data from a wide range of times and places. They consider the links between linguistic structure and social complexity and relate their findings to the causes and processes of language change. Their arguments are frequently controversial and provocative; their conclusions add up to an important challenge to conventional ideas about the nature of language. The authors write readably and accessibly with no recourse to unnecessary jargon. This fascinating book will appeal to all those interested in the interrelations between human nature, culture, and language.
“Information Theory and Language” is a collection of 12 articles that appeared recently in Entropy as part of a Special Issue of the same title. These contributions represent state-of-the-art interdisciplinary research at the interface of information theory and language studies. They concern in particular: • Applications of information theoretic concepts such as Shannon and Rényi entropies, mutual information, and rate–distortion curves to the research of natural languages; • Mathematical work in information theory inspired by natural language phenomena, such as deriving moments of subword complexity or proving continuity of mutual information; • Empirical and theoretical investigation of quantitative laws of natural language such as Zipf’s law, Herdan’s law, and Menzerath–Altmann’s law; • Empirical and theoretical investigations of statistical language models, including recently developed neural language models, their entropies, and other parameters; • Standardizing language resources for statistical investigation of natural language; • Other topics concerning semantics, syntax, and critical phenomena. Whereas the traditional divide between probabilistic and formal approaches to human language, cultivated in the disjoint scholarships of natural sciences and humanities, has been blurred in recent years, this book can contribute to pointing out potential areas of future research cross-fertilization.
This is the third supplementary volume to Kluwer's highly acclaimed twelve-volume Encyclopaedia of Mathematics. This additional volume contains nearly 500 new entries written by experts and covers developments and topics not included in the previous volumes. These entries are arranged alphabetically throughout and a detailed index is included. This supplementary volume enhances the existing twelve volumes, and together, these thirteen volumes represent the most authoritative, comprehensive and up-to-date Encyclopaedia of Mathematics available.
The organization of the lexicon, and especially the relations between groups of lexemes is a strongly debated topic in linguistics. Some authors have insisted on the lack of any structure of the lexicon. In this vein, Di Sciullo & Williams (1987: 3) claim that “[t]he lexicon is like a prison – it contains only the lawless, and the only thing that its inmates have in commonis lawlessness”. In the alternative view, the lexicon is assumed to have a rich structure that captures all regularities and partial regularities that exist between lexical entries.Two very different schools of linguistics have insisted on the organization of the lexicon. On the one hand, for theories like HPSG (Pollard & Sag 1994), but also some versions of construction grammar (Fillmore & Kay 1995), the lexicon is assumed to have a very rich structure which captures common grammatical properties between its members. In this approach, a type hierarchy organizes the lexicon according to common properties between items. For example, Koenig (1999: 4, among others), working from an HPSG perspective, claims that the lexicon “provides a unified model for partial regularties, medium-size generalizations, and truly productive processes”. On the other hand, from the perspective of usage-based linguistics, several authors have drawn attention to the fact that lexemes which share morphological or syntactic properties, tend to be organized in clusters of surface (phonological or semantic) similarity (Bybee & Slobin 1982; Skousen 1989; Eddington 1996). This approach, often called analogical, has developed highly accurate computational and non-computational models that can predict the classes to which lexemes belong. Like the organization of lexemes in type hierarchies, analogical relations between items help speakers to make sense of intricate systems, and reduce apparent complexity (Köpcke & Zubin 1984). Despite this core commonality, and despite the fact that most linguists seem to agree that analogy plays an important role in language, there has been remarkably little work on bringing together these two approaches. Formal grammar traditions have been very successful in capturing grammatical behaviour, but, in the process, have downplayed the role analogy plays in linguistics (Anderson 2015). In this work, I aim to change this state of affairs. First, by providing an explicit formalization of how analogy interacts with grammar, and second, by showing that analogical effects and relations closely mirror the structures in the lexicon. I will show that both formal grammar approaches, and usage-based analogical models, capture mutually compatible relations in the lexicon.