Expressing rhetorical relations in instructional text: a case study of the purpose relation
Computational Linguistics
Revision-based generation of natural language summaries providing historical background: corpus-based analysis, design, implementation and evaluation
Generating natural language explanations from large-scale knowledge bases
Generating natural language explanations from large-scale knowledge bases
Empirically designing and evaluating a new revision-based model for summary generation
Artificial Intelligence - Special volume on empirical methods
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This paper presents a quantitative evaluation of the portability to the stock market domain of the revision rule hierarchy used by the system STREAK to incrementally generate newswire sports summaries. The evaluation consists of searching a test corpus of stock market reports for sentence pairs whose (semantic and syntactic) structures respectively match the triggering condition and application result of each revision rule. The results show that at least 59% of all rule classes are fully portable, with at least another 7% partially portable.