The topic of temporal meaning in texts has received considerable attention in recent years from scholars in linguistics, logical semantics, cognitive science, and artificial intelligence. Representing Time in Natural Language offers a systematic and detailed account of how we use temporal information contained in a text or in discourse to reason about the flow of time, inferring the order in which events happened when this is not explicitly stated. A new representational system is designed to formalize an appropriately context-dependent notion of situated inference. The Dynamic Aspect Tree, representing temporal dependencies, constitutes a novel and important dynamic temporal logic, one that makes it easy to see "what follows when" from the information given in an ordinary English text.

Alice ter Meulen integrates current research in natural language semantics, with detailed analyses of English discourse, and logical tools from a variety of sources into an information theory that provides the foundation for computational systems to reason about change and the flow of time. The topic of temporal meaning in texts has received considerable attention in recent years from scholars in linguistics, logical semantics, cognitive science, and artificial intelligence. Representing Time in Natural Language offers a systematic and detailed account of how we use temporal information contained in a text or in discourse to reason about the flow of time, inferring the order in which events happened when this is not explicitly stated. A new representational toolkit is designed to formalize an appropriately context-dependent notion of situated inference. Dynamic Aspect Trees representing temporal dependencies constitute a novel and important dynamic temporal logic that makes it easy to see what follows when from the information given in an ordinary English text. Ter Meulen makes use of some of the fundamental assumptions of Situation Semantics and incorporates the dynamic methodology embodied in Discourse Representation Theory and in other dynamic logics into her temporal logic. The result is a computational inference system that can be applied across the board to fragments of natural languages.

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.

How can computers distinguish the coherent from the unintelligible, recognize new information in a sentence, or draw inferences from a natural language passage? Computational semantics is an exciting new field that seeks answers to these questions, and this volume is the first textbook wholly devoted to this growing subdiscipline. The book explains the underlying theoretical issues and fundamental techniques for computing semantic representations for fragments of natural language. This volume will be an essential text for computer scientists, linguists, and anyone interested in the development of computational semantics.

Natural Language is not only the most important means of communication between human beings, it is also used over historical periods for the pres- vation of cultural achievements and their transmission from one generation to the other. During the last few decades, the ?ood of digitalized information has been growing tremendously. This tendency will continue with the globali- tion of information societies and with the growing importance of national and international computer networks. This is one reason why the theoretical und- standing and the automated treatment of communication processes based on natural language have such a decisive social and economic impact. In this c- text, the semantic representation of knowledge originally formulated in natural language plays a central part, because it connects all components of natural language processing systems, be they the automatic understanding of natural language (analysis), the rational reasoning over knowledge bases, or the g- eration of natural language expressions from formal representations. This book presents a method for the semantic representation of natural l- guage expressions (texts, sentences, phrases, etc. ) which can be used as a u- versal knowledge representation paradigm in the human sciences, like lingu- tics, cognitive psychology, or philosophy of language, as well as in com- tational linguistics and in arti?cial intelligence. It is also an attempt to close the gap between these disciplines, which to a large extent are still working separately.

This volume contains a detailed, precise and clear semantic formalism designed to allow non-programmers such as linguists and literary specialists to represent elements of meaning which they must deal with in their research and teaching. At the same time, by its basis in a functional programming paradigm, it retains sufficient formal precision to support computational implementation. The formalism is designed to represent meaning as found at a variety of levels, including basic semantic units and relations, word meaning, sentence-level phenomena, and text-level meaning. By drawing on fundamental principles of program design, the proposed formalism is both easy to read and modify yet sufficiently powerful to allow for the representation of complex semantic phenomena. In this monograph, the authors introduce the formalism and show its basic structure, apply it to the analysis of the semantics of a variety of linguistic phenomena in both English and French, and use it to represent the semantics of a variety of texts ranging from single sentences, to textual excepts, to a full story.

Proposes robust onomasiological semantic formalism and applies it to a wide variety of linguistic phenomena.

No detailed description available for "Representation and Processing of Natural Language".

How to Show Things with Words is an interdisciplinary research study at the interface between linguistics and philosophy which sheds new light on the narrative-theoretical issue of proximal vs. distal stance adoption in discourse. Narrative distance ultimately depends on the epistemological source of the information conveyed, but English and other Indo-European languages have no inflectional systems for (en)coding that source of knowledge. To fill in the gap, speech act theory is (re)considered in the light of philosophical research on linguistic functions and a parallel is drawn between grammaticalized evidential categories and the objectifying acts of Husserl's phenomenology of constitution. These intuitive vs. signitive intentional acts do, indeed, roughly correspond to direct vs. indirect evidentiary forms and can be inferred from the temporal-perspectival organization of discourse by the so-called intimation or announcement function of language-systems. It turns out that perspectival immediacy requires tenses with overlapping event- and reference-points, but predictions of the sort are non-monotonic forms of reasoning defeasible by quantificational aspect distinctions, on the one hand, and inherent meaning considerations, on the other. To substantiate this claim, the bulk of the book provides an in-depth formal semantic account of tense, aspect and Aktionsart, interwoven with a detailed analysis of the cognitive processes associated with eventuality-description types. The book adresses an audience of linguists in general, formal semanticists, cognitive scientists, philosophers and narratologists with an interest in natural language semantics.