indirect-requests

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).