Detecting and Generating Ironic Comparisons: An Application of Creative Information Retrieval

Ironic utterances promise an expected meaning that never arrives, and deliver instead a meaning that exposes the failure of our expectations. Though they can appear contextually inappropriate, ironic statements succeed when they subvert their context of use, so it is the context rather than the utterance that is shown to be incongruous. Every ironic statement thus poses two related questions: the first, “what is unexpected about my meaning?” helps us answer the second, “what is unexpected about my context of use?”. Like metaphor, irony is not overtly marked, and relies instead on a listener’s understanding of stereotypical norms to unpack its true meaning. In this paper we consider how irony relies upon and subverts our stereotypical knowledge of a domain, and show how this knowledge can be exploited to both recognize and generate ironic similes for a topic.