A Hybrid Reasoning Model for Indirect Answers

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. 1. I N T R O D U C T I O N Imagine a discourse context for (1) in which R's use of just (ld) is intended to convey a No, i.e., that R is not going shopping tonight. (By convention, square brackets indicate that the enclosed text was not explicitly stated.) The part of R's response consisting of (ld) (le) is what we call an indirect answer to a Yes-No question, and if (lc) had been uttered, (lc) would have been called a