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Approaches to Realisation in Natural Language Generation

  • Chris Mellish
Part of the ESPRIT Basic Research Series book series (ESPRIT BASIC)

Abstract

There has been a great deal of good research done in natural language generation and current systems produce impressive performance, but, in common with other areas of Computational Linguistics, the field suffers from a plethora of approaches and notations. This makes it difficult to compare different pieces of work and, indeed, to determine whether different researchers have the same position about what kind of task generation is.

Natural language generation is commonly thought of as having two aspects, “deciding what to say” and “deciding how to say it”. This paper concentrates on the second aspect, the problem of realisation, and is a report of work in progress aimed at developing some formal foundations for discussing existing and potential work in this area. We present a formal characterisation of the realisation problem in natural language generation. This is used to introduce a set of design decisions that must be addressed in implementing a realisation system. We look at approaches to realisation based on DCGs, FUG, Systemic Grammar and Classification in terms of this framework. Each of these comes with a rather different view of the realisation task which can, however, be thought of as a special case of the more general framework we present.

Because it is a description of work in progress, this paper is necessarily brief and superficial in places. We hope, however, that it does give an impression of how work on the formal foundations of Computational Linguistics can help us to understand and compare pieces of existing work and suggest possible lines of further development.

Keywords

Syntactic Structure Semantic Structure Horn Clause Computational Linguistics Formal Foundation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© ECSC - EEC - EAEC, Brussels - Luxembourg 1991

Authors and Affiliations

  • Chris Mellish
    • 1
  1. 1.Department of Artificial IntelligenceUniversity of EdinburghUK

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