This 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.
@article{arxiv.cmp-lg/9406014,
title = {A Hybrid Reasoning Model for Indirect Answers},
author = {Nancy Green and Sandra Carberry},
journal= {arXiv preprint arXiv:cmp-lg/9406014},
year = {2008}
}
Comments
To appear in Proc. of ACL-94. 8 pages, uuencoded compressed Postscript file; extract with Unix uudecode and uncompress. Contact Author for latex version