Pragmatics and natural language generation
Artificial Intelligence
Communicative acts for explanation generation
International Journal of Man-Machine Studies
A problem for RST: the need for multi-level discourse analysis
Computational Linguistics
A computational theory of goal-directed style in syntax
Computational Linguistics
Planning text for advisory dialogues: capturing intentional and rhetorical information
Computational Linguistics
A plan-based analysis of indirect speech acts
Computational Linguistics
Exploiting conversational implicature for generating concise explanations
EACL '91 Proceedings of the fifth conference on European chapter of the Association for Computational Linguistics
A hybrid reasoning model for indirect answers
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Planning coherent multisentential text
ACL '88 Proceedings of the 26th annual meeting on Association for Computational Linguistics
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An indirect answer to a Yes-No question conversationally implicates the speaker's evaluation of the truth of the questioned proposition. We present the approach to generation used in our implemented system for generating and interpreting indirect answers to Yes-No questions in English. Generation of a discourse plan is performed in two phases: content planning and plan pruning. During content planning, stimulus conditions are used to trigger speaker goals to include appropriate extra information with the direct answer. Plan pruning determines what parts of this full response do not need to be stated explicitly - resulting in, in appropriate discourse contexts, the generation of an indirect answer.