This book covers topics in formal linguistics, intonational phonology, computational linguistics, and experimental psycholinguistics, presenting them as an integrated theory of the language faculty. In this book Mark Steedman argues that the surface syntax of natural languages maps spoken and written forms directly to a compositional semantic representation that includes predicate-argument structure, quantification, and information structure without constructing any intervening structural representation. His purpose is to construct a principled theory of natural grammar that is directly compatible with both explanatory linguistic accounts of a number of problematic syntactic phenomena and a straightforward computational account of the way sentences are mapped onto representations of meaning. The radical nature of Steedman's proposal stems from his claim that much of the apparent complexity of syntax, prosody, and processing follows from the lexical specification of the grammar and from the involvement of a small number of universal rule-types for combining predicates and arguments. These syntactic operations are related to the combinators of Combinatory Logic, engendering a much freer definition of derivational constituency than is traditionally assumed. This property allows Combinatory Categorial Grammar to capture elegantly the structure and interpretation of coordination and intonation contour in English as well as some well-known interactions between word order, coordination, and relativization across a number of other languages. It also allows more direct compatibility with incremental semantic interpretation during parsing. The book covers topics in formal linguistics, intonational phonology, computational linguistics, and experimental psycholinguistics, presenting them as an integrated theory of the language faculty in a form accessible to readers from any of those fields.

This book covers topics in formal linguistics, intonational phonology, computational linguistics, and experimental psycholinguistics, presenting them as an integrated theory of the language faculty. In this book Mark Steedman argues that the surface syntax of natural languages maps spoken and written forms directly to a compositional semantic representation that includes predicate-argument structure, quantification, and information structure without constructing any intervening structural representation. His purpose is to construct a principled theory of natural grammar that is directly compatible with both explanatory linguistic accounts of a number of problematic syntactic phenomena and a straightforward computational account of the way sentences are mapped onto representations of meaning. The radical nature of Steedman's proposal stems from his claim that much of the apparent complexity of syntax, prosody, and processing follows from the lexical specification of the grammar and from the involvement of a small number of universal rule-types for combining predicates and arguments. These syntactic operations are related to the combinators of Combinatory Logic, engendering a much freer definition of derivational constituency than is traditionally assumed. This property allows Combinatory Categorial Grammar to capture elegantly the structure and interpretation of coordination and intonation contour in English as well as some well-known interactions between word order, coordination, and relativization across a number of other languages. It also allows more direct compatibility with incremental semantic interpretation during parsing. The book covers topics in formal linguistics, intonational phonology, computational linguistics, and experimental psycholinguistics, presenting them as an integrated theory of the language faculty in a form accessible to readers from any of those fields.

This volume deals with research on the processing of a native language, second language learning, bilingualism, typical and impaired syntax processing. The articles presented here cover a number of linguistic phenomena, including passives, temporal concord, object pronouns, reflexives, embedded sentences, relative clauses, wh-movement, and binding theory. They also apply various experimental methods, such as eye tracking, reaction times, event-related potentials, picture selection tasks, sentence elicitation, pupillometry, and picture matching tasks. As such, this book details a number of the most representative methods used in language processing.

No detailed description available for "Syntactic Structures".

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.

Leverage the power of machine learning and deep learning to extract information from text data About This Book Implement Machine Learning and Deep Learning techniques for efficient natural language processing Get started with NLTK and implement NLP in your applications with ease Understand and interpret human languages with the power of text analysis via Python Who This Book Is For This book is intended for Python developers who wish to start with natural language processing and want to make their applications smarter by implementing NLP in them. What You Will Learn Focus on Python programming paradigms, which are used to develop NLP applications Understand corpus analysis and different types of data attribute. Learn NLP using Python libraries such as NLTK, Polyglot, SpaCy, Standford CoreNLP and so on Learn about Features Extraction and Feature selection as part of Features Engineering. Explore the advantages of vectorization in Deep Learning. Get a better understanding of the architecture of a rule-based system. Optimize and fine-tune Supervised and Unsupervised Machine Learning algorithms for NLP problems. Identify Deep Learning techniques for Natural Language Processing and Natural Language Generation problems. In Detail This book starts off by laying the foundation for Natural Language Processing and why Python is one of the best options to build an NLP-based expert system with advantages such as Community support, availability of frameworks and so on. Later it gives you a better understanding of available free forms of corpus and different types of dataset. After this, you will know how to choose a dataset for natural language processing applications and find the right NLP techniques to process sentences in datasets and understand their structure. You will also learn how to tokenize different parts of sentences and ways to analyze them. During the course of the book, you will explore the semantic as well as syntactic analysis of text. You will understand how to solve various ambiguities in processing human language and will come across various scenarios while performing text analysis. You will learn the very basics of getting the environment ready for natural language processing, move on to the initial setup, and then quickly understand sentences and language parts. You will learn the power of Machine Learning and Deep Learning to extract information from text data. By the end of the book, you will have a clear understanding of natural language processing and will have worked on multiple examples that implement NLP in the real world. Style and approach This book teaches the readers various aspects of natural language Processing using NLTK. It takes the reader from the basic to advance level in a smooth way.

An Introduction to Syntactic Analysis and Theory offers beginning students a comprehensive overview of and introduction to our current understanding of the rules and principles that govern the syntax of natural languages. Includes numerous pedagogical features such as 'practice' boxes and sidebars, designed to facilitate understanding of both the 'hows' and the 'whys' of sentence structure Guides readers through syntactic and morphological structures in a progressive manner Takes the mystery out of one of the most crucial aspects of the workings of language – the principles and processes behind the structure of sentences Ideal for students with minimal knowledge of current syntactic research, it progresses in theoretical difficulty from basic ideas and theories to more complex and advanced, up to date concepts in syntactic theory