Proceedings of the Seventh Conference (AISB89) on Artificial Intelligence and Simulation of Behaviour
Towards a Computational Theory of Definite Anaphora Comprehension in English Discourse
Towards a Computational Theory of Definite Anaphora Comprehension in English Discourse
Generating natural language text in response to questions about database structure
Generating natural language text in response to questions about database structure
Computer generation of multiparagraph English text
Computational Linguistics
Computational Linguistics
EACL '89 Proceedings of the fourth conference on European chapter of the Association for Computational Linguistics
Functional Unification Grammar: a formalism for machine translation
ACL '84 Proceedings of the 10th International Conference on Computational Linguistics and 22nd annual meeting on Association for Computational Linguistics
Salience: the key to the selection problem in natural language generation
ACL '82 Proceedings of the 20th annual meeting on Association for Computational Linguistics
Expressing rhetorical relations in instructional text: a case study of the purpose relation
Computational Linguistics
Generating inference-rich discourse through revisions of RST-Trees
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Cooperative plan identification: constructing concise and effective plan descriptions
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Artificial Intelligence Review
Learning domain knowledge for teaching procedural skills
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
Use of series parallel digraph analysis in generating instructions for multiple users
VIP '00 Selected papers from the Pan-Sydney workshop on Visualisation - Volume 2
Use of directed acyclic graph analysis in generating instructions for multiple users
APVis '01 Proceedings of the 2001 Asia-Pacific symposium on Information visualisation - Volume 9
Automated knowledge acquisition for instructional text generation
Proceedings of the 20th annual international conference on Computer documentation
Generating Natural Language Descriptions of Project Plans
AI '99 Proceedings of the 12th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
Presenting Mathematical Concepts as an Example for Inference-Rich Domains
NLDB '00 Proceedings of the 5th International Conference on Applications of Natural Language to Information Systems-Revised Papers
A corpus study of negative imperatives in natural language instructions
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Content and rhetorical status selection in instructional texts
INLG '94 Proceedings of the Seventh International Workshop on Natural Language Generation
Using plan reasoning in the generation of plan descriptions
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
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This paper addresses the problem of designing a system that accepts a plan structure of the sort generated by AI planning programs and produces natural language text explaining how to execute the plan. We describe a system that generates text from plans produced by the NONLIN planner (Tate 1976).The results of our system are promising, but the texts still lack much of the smoothness of human-generated text. This is partly because, although the domain of plans seems a priori to provide rich structure that a natural language generator can use, in practice a plan that is generated without the production of explanations in mind rarely contains the kinds of information that would yield an interesting natural language account. For instance, the hierarchical organization assigned to a plan is liable to reflect more a programmer's approach to generating a class of plans efficiently than the way that a human would naturally "chunk" the relevant actions. Such problems are, of course, similar to those that Swartout (1983) encountered with expert systems. In addition, AI planners have a restricted view of the world that is hard to match up with the normal semantics of natural language expressions. Thus constructs that are primitive to the planner may be only clumsily or misleadingly expressed in natural language, and the range of possible natural language constructs may be artificially limited by the shallowness of the planner's representations.