Agreement is a pervasive phenomenon across natural languages. Depending on one’s definition of what constitutes agreement, it is either found in virtually every natural language that we know of, or it is at least found in a great many. Either way, it seems to be a core part of the system that underpins our syntactic knowledge. Since the introduction of the operation of Agree in Chomsky (2000), agreement phenomena and the mechanism that underlies agreement have garnered a lot of attention in the Minimalist literature and have received different theoretical treatments at different stages. Since then, many different phenomena involving dependencies between elements in syntax, including movement or not, have been accounted for using Agree. The mechanism of Agree thus provides a powerful tool to model dependencies between syntactic elements far beyond φ-feature agreement. The articles collected in this volume further explore these topics and contribute to the ongoing debates surrounding agreement. The authors gathered in this book are internationally reknown experts in the field of Agreement.

'Agreement' is the grammatical phenomenon in which the form of one item, such as the noun 'horses', forces a second item in the sentence, such as the verb 'gallop', to appear in a particular form, i.e. 'gallop' must agree with 'horses' in number. Even though agreement phenomena are some of the most familiar and well-studied aspects of grammar, there are certain basic questions that have rarely been asked, let alone answered. This book develops a theory of the agreement processes found in language, and considers why verbs agree with subjects in person, adjectives agree in number and gender but not person, and nouns do not agree at all. Explaining these differences leads to a theory that can be applied to all parts of speech and to all languages.

Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective

Although grammatical agreement or concord is widespread in human languages, linguistic theorists have generally treated agreement phenomena as secondary or even marginal. All the papers in this volume, however, take agreement phenomena seriously, as presenting either a general issue in theory construction or a descriptive problem in particular types of languages. The theoretical perspectives range from purportedly theory-neutral typological frameworks to assumptions about the validity of one or another current formal model. Further, the degree of generality ranges from a universalist nature-of-human-language agenda to concern with one or another aspect of grammatical agreement or with agreement in a single language or language group.

This book investigates the historical paths leading from pronouns to markers of verbal agreement and proposes a unified formal account of this grammaticalization process. In opposition to beliefs widely held in the literature, it is argued that new agreement formatives can be coined in a multitude of syntactic environments. Still, the individual paths toward agreement are shown to exhibit a set of underlying similarities which are attributed to universal principles that govern the reanalysis of pronominal clitics as exponents of verbal agreement across languages. It is claimed that syntactic principles impose only a set of necessary conditions on the reanalysis in question, while its ultimate trigger is morphological in nature. More specifically, it is argued that the acquisition of inflectional morphology is governed by blocking effects which operate during language acquisition and promote the grammaticalization of new markers if this change serves to replace ‘worn-out’, underspecified forms with new, more specified candidates.

Many NLP tasks have at their core a subtask of extracting the dependencies—who did what to whom—from natural language sentences. This task can be understood as the inverse of the problem solved in different ways by diverse human languages, namely, how to indicate the relationship between different parts of a sentence. Understanding how languages solve the problem can be extremely useful in both feature design and error analysis in the application of machine learning to NLP. Likewise, understanding cross-linguistic variation can be important for the design of MT systems and other multilingual applications. The purpose of this book is to present in a succinct and accessible fashion information about the morphological and syntactic structure of human languages that can be useful in creating more linguistically sophisticated, more language-independent, and thus more successful NLP systems. Table of Contents: Acknowledgments / Introduction/motivation / Morphology: Introduction / Morphophonology / Morphosyntax / Syntax: Introduction / Parts of speech / Heads, arguments, and adjuncts / Argument types and grammatical functions / Mismatches between syntactic position and semantic roles / Resources / Bibliography / Author's Biography / General Index / Index of Languages

Research into Natural Language Processing - the use of computers to process language - has developed over the last couple of decades into one of the most vigorous and interesting areas of current work on language and communication. This book introduces the subject through the discussion and development of various computer programs which illustrate some of the basic concepts and techniques in the field. The programming language used is Prolog, which is especially well-suited for Natural Language Processing and those with little or no background in computing. Following the general introduction, the first section of the book presents Prolog, and the following chapters illustrate how various Natural Language Processing programs may be written using this programming language. Since it is assumed that the reader has no previous experience in programming, great care is taken to provide a simple yet comprehensive introduction to Prolog. Due to the 'user friendly' nature of Prolog, simple yet effective programs may be written from an early stage. The reader is gradually introduced to various techniques for syntactic processing, ranging from Finite State Network recognisors to Chart parsers. An integral element of the book is the comprehensive set of exercises included in each chapter as a means of cementing the reader's understanding of each topic. Suggested answers are also provided. An Introduction to Natural Language Processing Through Prolog is an excellent introduction to the subject for students of linguistics and computer science, and will be especially useful for those with no background in the subject.