Biblical Current Events is a sixteen week study guide program that is designed to inform people about Bible prophecy and how it relates to today's current events. The study compares the news of today with scripture to encourage discussion and prayer about such topics as, the economy, education and morality.
The authors present a social linguistic/social interactional approach to the discourse analysis of classroom language and literacy events. Building on recent theories in interactional sociolinguistics, literary theory, social anthropology, critical discourse analysis, and the New Literacy Studies, they describe a microethnographic approach to discourse analysis that provides a reflexive and recursive research process that continually questions what counts as knowledge in and of the interactions among teachers and students. The approach combines attention to how people use language and other systems of communication in constructing classroom events with attention to social, cultural, and political processes. The focus of attention is on actual people acting and reacting to each other, creating and recreating the worlds in which they live. One contribution of the microethnographic approach is to highlight the conception of people as complex, multi-dimensional actors who together use what is given by culture, language, social, and economic capital to create new meanings, social relationships and possibilities, and to recreate culture and language. The approach presented by the authors does not separate methodological, theoretical, and epistemological issues. Instead, they argue that research always involves a dialectical relationship among the object of the research, the theoretical frameworks and methodologies driving the research, and the situations within which the research is being conducted.
The book offers a detailed guide to temporal ordering, exploring open problems in the field and providing solutions and extensive analysis. It addresses the challenge of automatically ordering events and times in text. Aided by TimeML, it also describes and presents concepts relating to time in easy-to-compute terms. Working out the order that events and times happen has proven difficult for computers, since the language used to discuss time can be vague and complex. Mapping out these concepts for a computational system, which does not have its own inherent idea of time, is, unsurprisingly, tough. Solving this problem enables powerful systems that can plan, reason about events, and construct stories of their own accord, as well as understand the complex narratives that humans express and comprehend so naturally.
This book presents a theory and data-driven analysis of temporal ordering, leading to the identification of exactly what is difficult about the task. It then proposes and evaluates machine-learning solutions for the major difficulties.
It is a valuable resource for those working in machine learning for natural language processing as well as anyone studying time in language, or involved in annotating the structure of time in documents.
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