This book explains how to build Natural Language Generation (NLG) systems - computer software systems which use techniques from artificial intelligence and computational linguistics to automatically generate understandable texts in English ...

This book aims to provide a comprehensive overview of NLG, encompassing not only language models but also alternative approaches, user requirements, evaluation methods, safety and testing protocols, and practical applications.

Abstract: "Our experience in the IDAS natural language generation project has shown us that IDAS's KLONE-like classifier, originally built solely to hold a domain knowledge base, could also be used to perform many of the computations ...

Abstract: "The IDAS natural-language generation system uses a KL- ONE type classifier to perform content determination, surface realisation, and part of text planning.

Abstract: "Natural language generation systems should choose nouns by searching for lexical units that are (i) known to the user, (ii) truthfully describe the object being lexicalized; (iii) convey sufficient information to fulfill the ...

Abstract: "Referring expressions and other object descriptions should be maximal under the Local Brevity, No Unnecessary Components, and Lexical Preference preference rules; otherwise, they may lead hearers to infer unwanted conversational ...

Abstract: "The Intelligent Documentation Advisory System (IDAS) being constructed by Edinburgh University, Racal Intruments [sic] Ltd, Inference Europe Ltd and Racal Research Ltd must be able to generate 'how- to' instructions that are ...

Abstract: "We have developed two systems, FN and ANDD, that use natural language and graphical displays, respectively, to communicate information about objects to human users.

Abstract: "We simplify previous work in the development of algorithms for the generation of referring expressions while at the same time taking account of psycholinguistic findings and transcript data.