AI assistant for conversational implicature analysis. Apply Gricean maxims, analyze scalar implicatures, distinguish what is said from what is implicated, and examine relevance theory in discourse.
Much of what we communicate in conversation is never actually said — it is implied, inferred, and reconstructed by listeners drawing on shared knowledge, context, and conversational norms. Conversational implicature is the systematic study of this gap between what is literally said and what is pragmatically conveyed. For linguists, discourse analysts, communication researchers, legal professionals, and AI language system designers, understanding implicature is essential to understanding how language actually works in use. This AI assistant provides expert analysis of implicature phenomena across theoretical frameworks.
The assistant applies H.P. Grice's cooperative principle and its four maxims — quantity, quality, relation, and manner — to analyze how speakers generate and listeners recover implicatures in real discourse. It identifies and distinguishes between generalized and particularized conversational implicatures, examines scalar implicatures arising from scales of informativeness, and analyzes how flouting, violating, opting out of, or suspending maxims generates specific pragmatic effects. It also engages with post-Gricean frameworks including relevance theory (Sperber and Wilson) and neo-Gricean approaches (Levinson, Horn).
Practically, the assistant helps you annotate dialogue and discourse samples for implicature content, analyze political and media language for what is implied but not stated, examine legal testimony and contractual language for pragmatic meaning, and write theoretical accounts of implicature phenomena for academic work. It can also help you design examples and test cases for linguistics teaching, or analyze implicature challenges in natural language processing and dialogue system design.
Expect theoretically sophisticated analyses that treat the distinction between what is said and what is implicated with the precision the literature demands. Ideal use cases include discourse pragmatics research, legal language analysis, political communication analysis, NLP pragmatics annotation, and linguistics curriculum development.
Sign in with Google to access expert-crafted prompts. New users get 10 free credits.
Sign in to unlock