Building natural language generation systems
Building natural language generation systems
A Practical Guide to Knowledge Acquisition
A Practical Guide to Knowledge Acquisition
Using Natural-Language Processing to Produce Weather Forecasts
IEEE Expert: Intelligent Systems and Their Applications
Pipelines and size constraints
Computational Linguistics
Practical issues in automatic documentation generation
ANLC '94 Proceedings of the fourth conference on Applied natural language processing
Customizable descriptions of object-oriented models
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Squibs and discussions: human variation and lexical choice
Computational Linguistics - Summarization
Lessons from a failure: generating tailored smoking cessation letters
Artificial Intelligence
Using a randomised controlled clinical trial to evaluate an NLG system
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Choosing words in computer-generated weather forecasts
Artificial Intelligence - Special volume on connecting language to the world
A two-stage model for content determination
EWNLG '01 Proceedings of the 8th European workshop on Natural Language Generation - Volume 8
Learning the meaning and usage of time phrases from a parallel text-data corpus
HLT-NAACL-LWM '04 Proceedings of the HLT-NAACL 2003 workshop on Learning word meaning from non-linguistic data - Volume 6
Statistical acquisition of content selection rules for natural language generation
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
A comparison of hedged and non-hedged NLG texts
ENLG '07 Proceedings of the Eleventh European Workshop on Natural Language Generation
Acquiring correct knowledge for natural language generation
Journal of Artificial Intelligence Research
Choosing words in computer-generated weather forecasts
Artificial Intelligence - Special volume on connecting language to the world
Generating affective natural language for parents of neonatal infants
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
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We describe the knowledge acquisition (KA) techniques used to build the STOP system, especially sorting and think-aloud protocols. That is, we describe the ways in which we interacted with domain experts to determine appropriate user categories, schemas, detailed content rules, and so forth for STOP. Informal evaluations of these techniques suggest that they had some benefit, but perhaps were most successful as a source of insight and hypotheses, and should ideally have been supplemented by other techniques when deciding on the specific rules and knowledge incorporated into STOP.