Building natural language generation systems
Building natural language generation systems
Planning English Sentences
Lessons from a failure: generating tailored smoking cessation letters
Artificial Intelligence
Generating intelligent numerical answers in a question-answering system
INLG '06 Proceedings of the Fourth International Natural Language Generation Conference
KR4HC'09 Proceedings of the 2009 AIME international conference on Knowledge Representation for Health-Care: data, Processes and Guidelines
If it may have happened before, it happened, but not necessarily before
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
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This paper describes a model of the choice of modal verbs and modal particles. The choice mechanism does not require a modality-specific input as, e.g., a modal logical formula. Instead semantic (modal force) and pragmatic constraints (speech act marking) are applied to the available information on the whole and constrain the set of modal candidates to those that are appropriate in the respective contexts. The choice model is realized in the CAN system that generates recommendations about courses of study.