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Why do speakers of all languages use different grammatical structures under different communicative circumstances to express the same idea? Professor Lambrecht explores the relationship between the structure of the sentence and the linguistic and extra-linguistic context in which it is used. His analysis is based on the observation that the structure of a sentence reflects a speaker's assumption about the hearer's state of knowledge and consciousness at the time of the utterance. This relationship between speaker assumptions and formal sentence structure is governed by rules and conventions of grammar, in a component called 'information structure'. Four independent but interrelated categories are analysed: presupposition and assertion, identifiability and activation, topic, and focus.
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The architecture of the human language faculty has been one of the main foci of the linguistic research of the last half century. This branch of linguistics, broadly known as Generative Grammar, is concerned with the formulation of explanatory formal accounts of linguistic phenomena with the ulterior goal of gaining insight into the properties of the 'language organ'. The series comprises high quality monographs and collected volumes that address such issues. The topics in this series range from phonology to semantics, from syntax to information structure, from mathematical linguistics to studies of the lexicon. To discuss your book idea or submit a proposal, please contact Birgit Sievert
The contributions of this thematic collection center around the typology of pronominal paradigms, the generation of syntactic and semantic representations for constructions containing pronouns, and the neurological underpinnings for linguistic distinctions that are relevant for the production and interpretation of these constructions. They come from different theoretical approaches and methodological backgrounds and take into account data from a wide range of Indoeuropean and non-Indoeuropean languages. Bringing together a cross-section of recent research on the grammar and representation of pronouns, the volume offers a kaleidoscope of studies united by the common topic of pronouns as a domain of language that exemplarily shows the interaction of different components responsible for computational (syntactic and semantic), lexical, and discourse-pragmatic processes.
The papers in this volume examine the current role of grammatical functions in transformational syntax in two ways: (i) through largely theoretical considerations of their status, and (ii) through detailed analyses for a wide variety of languages. Taken together the chapters in this volume present a comprehensive view of how transformational syntax characterizes the elusive but often useful notions of subject and object, examining how subject and object properties are distributed among various functional projections, converging sometimes in particular languages.
Analyzing Grammar is a clear introductory textbook on grammatical analysis, designed for students beginning to study the discipline. Covering both syntax (the structure of phrases and sentences) and morphology (the structure of words), it equips them with the tools and methods needed to analyze grammatical patterns in any language. Students are shown how to use standard notational devices such as phrase structure trees and word-formation rules, as well as prose descriptions. Emphasis is placed on comparing the different grammatical systems of the world's languages, and students are encouraged to practice the analyses through a diverse range of problem sets and exercises. Topics covered include word order, constituency, case, agreement, tense, gender, pronoun systems, inflection, derivation, argument structure and grammatical relations, and a useful glossary provides a clear explanation of each term. Accessibly written and comprehensive, Analyzing Grammar is set to become a key text for all courses in grammatical analysis.
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.
Syntax – the study of sentence structure – has been at the centre of generative linguistics from its inception and has developed rapidly and in various directions. The Cambridge Handbook of Generative Syntax provides a historical context for what is happening in the field of generative syntax today, a survey of the various generative approaches to syntactic structure available in the literature and an overview of the state of the art in the principal modules of the theory and the interfaces with semantics, phonology, information structure and sentence processing, as well as linguistic variation and language acquisition. This indispensable resource for advanced students, professional linguists (generative and non-generative alike) and scholars in related fields of inquiry presents a comprehensive survey of the field of generative syntactic research in all its variety, written by leading experts and providing a proper sense of the range of syntactic theories calling themselves generative.