A Hybrid Reasoning Model for Indirect Answers

dc.creatorGreen, Nancy
dc.creatorCarberry, Sandra
dc.date1994-06-07
dc.date.accessioned2026-07-07T09:09:20Z
dc.date.available2026-07-07T09:09:20Z
dc.descriptionThis paper presents our implemented computational model for interpreting and generating indirect answers to Yes-No questions. Its main features are 1) a discourse-plan-based approach to implicature, 2) a reversible architecture for generation and interpretation, 3) a hybrid reasoning model that employs both plan inference and logical inference, and 4) use of stimulus conditions to model a speaker's motivation for providing appropriate, unrequested information. The model handles a wider range of types of indirect answers than previous computational models and has several significant advantages.
dc.descriptionTo appear in Proc. of ACL-94. 8 pages, uuencoded compressed Postscript file; extract with Unix uudecode and uncompress. Contact Author for latex version
dc.identifierhttps://arxiv.org/abs/cmp-lg/9406014
dc.identifierhttp://arxiv.org/abs/cmp-lg/9406014
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/150998
dc.subjectComputation and Language
dc.titleA Hybrid Reasoning Model for Indirect Answers
dc.typetext

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