A Flexible Shallow Approach to Text Generation

Stephan Busemann, Helmut Horacek

In: Eduard Hovy (Hrsg.). 9th International Natural Language Generation Workshop. International Natural Language Generation Conference (INLG-98) August 5-7 Niagara-on-the-Lake ON Canada Seiten 238-247 1998.


In order to support the efficient development of NL generation systems, two orthogonal methods are currently pursued with emphasis: (1) reusable, general, and linguistically motivated surface realization components, and (2) simple, task-oriented template-based techniques. In this paper we argue that, from an application-oriented perspective, the benefits of both are still limited. In order to improve this situation, we suggest and evaluate shallow generation methods associated with increased flexibility. We advise a close connection between domain-motivated and linguistic ontologies that supports the quick adaptation to new tasks and domains, rather than the reuse of general resources. Our method is especially designed for generating reports with limited linguistic variations.

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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence