Reference production, often termed Referring Expression Generation (REG) in computational linguistics, encompasses two distinct tasks: (1) one-shot REG, and (2) REG-in-context. One-shot REG explores which properties of a referent offer a unique description of it. In contrast, REG-in-context asks which (anaphoric) referring expressions are optimal at various points in discourse. This book offers a series of in-depth studies of the REG-in-context task. It thoroughly explores various aspects of the task such as corpus selection, computational methods, feature analysis, and evaluation techniques. The comparative study of different corpora highlights the pivotal role of corpus choice in REG-in-context research, emphasizing its influence on all subsequent model development steps. An experimental analysis of various feature-based machine learning models reveals that those with a concise set of linguistically-informed features can rival models with more features. Furthermore, this work highlights the importance of paragraph-related concepts, an area underexplored in Natural Language Generation (NLG). The book offers a thorough evaluation of different approaches to the REG-in-context task (rule-based, feature-based, and neural end-to-end), and demonstrates that well-crafted, non-neural models are capable of matching or surpassing the performance of neural REG-in-context models. In addition, the book delves into post-hoc experiments, aimed at improving the explainability of both neural and classical REG-in-context models. It also addresses other critical topics, such as the limitations of accuracy-based evaluation metrics and the essential role of human evaluation in NLG research. These studies collectively advance our understanding of REG-in-context. They highlight the importance of selecting appropriate corpora and targeted features. They show the need for context-aware modeling and the value of a comprehensive approach to model evaluation and interpretation. This detailed analysis of REG-in-context paves the way for developing more sophisticated, linguistically-informed, and contextually appropriate NLG systems.

This handbook presents an overview of the phenomenon of reference - the ability to refer to and pick out entities - which is an essential part of human language and cognition. In the volume's 21 chapters, international experts in the field offer a critical account of all aspects of reference from a range of theoretical perspectives. Chapters in the first part of the book are concerned with basic questions related to different types of referring expression and their interpretation. They address questions about the role of the speaker - including speaker intentions - and of the addressee, as well as the role played by the semantics of the linguistic forms themselves in establishing reference. This part also explores the nature of such concepts as definite and indefinite reference and specificity, and the conditions under which reference may fail. The second part of the volume looks at implications and applications, with chapters covering such topics as the acquisition of reference by children, the processing of reference both in the human brain and by machines. The volume will be of interest to linguists in a wide range of subfields, including semantics, pragmatics, computational linguistics, and psycho- and neurolinguistics, as well as scholars in related fields such as philosophy and computer science.

To communicate, speakers need to make it clear what they are talking about. Referring expressions play a crucial part in achieving this, by anchoring utterances to things. Examples of referring expressions include noun phrases such as “this phenomenon”, “it” and “the phenomenon to which this Topic is devoted”. Reference is studied throughout the Cognitive Sciences (from philosophy and logic to neuro-psychology, computer science and linguistics), because it is thought to lie at the core of all of communication. Recent years have seen a new wave of work on models of referring, as witnessed by a number of recent research projects, books, and journal Special Issues. The Research Topic “Models of Reference” in Frontiers in Psychology is a new milestone, focusing on contributions from Psycholinguistics and Computational Linguistics. The articles in it are concerned with such issues as audience design, overspecification, visual perception, and variation between speakers.

This book constitutes the proceedings of the 8th International and Interdisciplinary Conference on Modeling and Using Context, CONTEXT 2013, held in Annecy, France, in October/November 2013. The 23 full papers and 9 short papers presented were carefully reviewed and selected from numerous submissions. In addition the book contains two keynote speeches and 9 poster papers. They cover cutting-edge results from the wide range of disciplines concerned with context, including: Cognitive Sciences (Linguistics, Psychology, Computer Science, Neuroscience), and computer science (artificial intelligence, logics, ubiquitous and pervasive computing, context-awareness systems), and the Social Sciences and Organizational Sciences, as well as the Humanities and all application areas, including Medicine and Law.

Natural language generation (NLG) is a subfield of natural language processing (NLP) that is often characterized as the study of automatically converting non-linguistic representations (e.g., from databases or other knowledge sources) into coherent natural language text. In recent years the field has evolved substantially. Perhaps the most important new development is the current emphasis on data-oriented methods and empirical evaluation. Progress in related areas such as machine translation, dialogue system design and automatic text summarization and the resulting awareness of the importance of language generation, the increasing availability of suitable corpora in recent years, and the organization of shared tasks for NLG, where different teams of researchers develop and evaluate their algorithms on a shared, held out data set have had a considerable impact on the field, and this book offers the first comprehensive overview of recent empirically oriented NLG research.

A comprehensive overview of the state-of-the-art in natural language generation for interactive systems, with links to resources for further research.

8.6 Issues Raised by the Algorithms Proposed

This book constitutes the refereed proceedings of the 6th International Conference on Logical Aspects of Computational Linguistics, LACL 2011, held in Montpellier, France, in June/July 2011. The 18 revised full papers presented were carefully reviewed and selected from 31 submissions. The papers address a wide range of logical and formal methods in computational linguistics such as type-theoretic grammars, dependency grammars, formal language theory, grammatical inference, minimalism, generation, and lexical and formal semantics.

This book considers how people talk about their environment, find their way in new surroundings, and plan routes. Part I explores the empirical insights gained from research in the cognitive underpinnings of spatial representation in language. Part II proposes solutions for capturing such insights formally, and in Part III authors discuss how theory is put into practice through spatial assistance systems. These three perspectives stem from research disciplines which deal with the spatial domain in different ways, and which often remain separate. In this book they are combined so as to highlight both the state of the art in the field and the benefit of building bridges between methodologies and disciplines. Finding our way and planning routes is relevant to us all; this book ultimately helps improve our everyday lives.