Text Polishing: Surface-Oriented Smoothing of Generated Text via Markup-Based Revision Rules
نویسنده
چکیده
In this paper, we introduce text polishing, a novel, surface-oriented approach to using revisions in natural language generation in order to improve the fluency of generated texts. In this approach, markupbased revision rules are used to implement sentence planning operations such as aggregation, referring expression generation and discourse marker insertion. By working close to the surface, we suggest that it becomes easier to partially automate the acquisition of revision rules, and that it becomes possible to improve the scalability of template-based generation systems. We describe our current implementation, including an initial evaluation of a tool for bootstrapping revision rules from examples, and conclude with a discussion of related work.
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