indirect-requests

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IndirectRequests is an LLM-generated dataset of user utterances in a task-oriented dialogue setting where the user does not directly specify their preferred slot value. IndirectRequests was generated by crowdsourcing human labels over a dataset generated using a combination of GPT-3.5 (turbo) and GPT-4. Each utterance is labelled along two dimensions: World Understanding (the degree of world understanding it takes to understand the utterance) Unambiguity (whether or not the generated utterance unambiguously entails a single target slot value among a set of candidate possible values).