Reiter E., Dale R. Building Natural Language Generation Systems

Издательство Cambridge University Press, 2000, -272 pp.This book describes NATURAL LANGUAGE GENERATION (NLG), which is a subfield of artificial intelligence and computational linguistics that is concerned with building computer software systems that can produce meaningful texts in English or other human languages from some underlying nonlinguistic representation of information. NLG systems use knowledge about language and the application domain to automatically produce documents, reports, help messages, and other kinds of texts.
As we enter the new millennium, work in natural language processing, and in particular natural language generation, is at an exciting stage in its development. The mid- to late 1990s have seen the emergence of the first fielded NLG applications, and the first software houses specialising in the development of NLG technology. At the time of writing, only a handful of systems are in everyday use, but many more are under development and should be fielded within the next few years. The growing interest in applications of the technology has also changed the nature of academic research in the field. More attention is now being paid to software engineering issues, and to using NLG within a wider document generation process that incorporates graphical elements and other realities of the Web-based information age such as hypertext links.
However, despite the growing interest in NLG in general and applied NLG in particular, it is often difficult for people who are not already knowledgeable in the field to obtain a comprehensive overview of what is involved in building a natural language generation system. There are no existing textbooks on NLG; most books in the area are either revised doctoral dissertations or edited collections derived from workshops and conferences. Textbooks in the broader area of natural language processing as a whole typically devote a single chapter to natural language generation. There are some very good review articles which provide overviews of work in NLG, but most of these concentrate on theoretical issues; and in any case, it is difficult to give a comprehensive overview of a field as rich as NLG in twenty or thirty pages.
The goals of this book are to fill this void and to provide a resource which describes NLG from the perspective of what is involved in building complete NLG systems. The book is intended to serve a number of audiences. We hope to meet the needs of the following communities:
Students should be able to use our book as a textbook for a postgraduate course in NLG, as supplemental reading in general courses on natural language processing, and as a general resource for learning about NLG in institutions where formal courses on the subject are not available. We know of many students who are interested in NLG but are discouraged by the fact that it is difficult to learn about the field; we hope that our book will encourage more students to pursue their interests in the area.
Academics working in related areas - such as natural language analysis, writing-support tools, and advanced hypertext technologies - can use our book to understand the goals, underlying theories, representations, and algorithms of NLG and how these relate to their own fields. We hope this will encourage more interaction and cross-fertilisation between NLG and these related areas.
Software developers working on applications which need to produce linguistic output, such as software that generates letters and reports, can use our book to understand what NLG has to offer in building such systems and how to incorporate the relevant aspects of NLG into these systems. We believe that one of the major impediments to the use of NLG in real systems is the difficulty of learning about the technology. A major goal for our book is to help remove this barrier.
Last but not least, we hope that the synthesis of NLG work presented here will help define a framework within which new and existing work in NLG can be discussed. It is often difficult to compare or combine results from the work of different researchers, because their work often is based on different assumptions about the inputs, outputs, and expected functionalities of the various components of an NLG system. The problems in reconciling these differences are sometimes exacerbated by a lack of relevant detail in the published research literature. In this book we present an NLG system architecture which embodies one particular set of assumptions about inputs, outputs, and the modularisation of functionality within an NLG system. Our aim is to provide a model that is sufficiently well specified that it can be used as a basis for comparison of alternatives.National Language Generation in Practice
The Architecture of a Natural Language Generation System
Document Planning
Microplanning
Surface Realisation
Beyond Text Generation
NLG Systems Mentioned in This Book