  We present a paradigm for extensible lexicon development based on Lexical
Conceptual Structure to support social engineering detection and response
generation. We leverage the central notions of ask (elicitation of behaviors
such as providing access to money) and framing (risk/reward implied by the
ask). We demonstrate improvements in ask/framing detection through refinements
to our lexical organization and show that response generation qualitatively
improves as ask/framing detection performance improves. The paradigm presents a
systematic and efficient approach to resource adaptation for improved
task-specific performance.
