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Framenets and constructiCons are applied instantiations of the linguistic frameworks known as Frame Semantics and Construction Grammar, respectively, in the form of computational, semiformally structured linguistic resources. The resources have a common history, both theoretically and in design: They are built as English-language resources in the framework of the Berkeley FrameNet initiative. They enjoy the double nature of being descriptive linguistic resources as well as finding frequent use in a computational linguistic context, where they have been used both in NLP applications and as underlying knowledge bases in areas such as computer-assisted language learning. The chapter provides a bird’s-eye view on these resources: their theoretical foundations; design principles and how they are compiled; theoretical and methodological interrelations; the challenges involved in building framenets and constructiCons for new languages and for cross-linguistic application; the differences and interactions between linguistic and computational linguistic work on framenets and constructiCons; application to language pedagogy; and outstanding theoretical and methodological issues.
AI can assist the linguist in doing research on the structure of language. This Element illustrates this possibility by showing how a conversational AI based on a Large Language Model (AI LLM chatbot) can assist the Construction Grammarian, and especially the Frame Semanticist. An AI LLM chatbot is a text-generation system trained on vast amounts of text. To generate text, it must be able to find patterns in the data and mimic some linguistic capacity, at least in the eyes of a cooperative human user. The authors do not focus on whether AIs “understand” language. Rather, they investigate whether AI LLM chatbots are useful tools for linguists. They reframe the discussion from what AI LLM chatbots can do with language to what they can do for linguists. They find that a chatty LLM can labor usefully as an eliciting interlocutor, and present precise, scripted routines for prompting conversational LLMs.
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