Persian Benchmark for Joint Intent Detection and Slot Filling: Overview

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The Persian benchmark for joint intent detection and slot filling is a valuable resource for researchers working on natural language understanding (NLU) tasks. This dataset provides a standardized platform for evaluating and comparing different models' ability to simultaneously identify the user's intent and extract relevant information (slots) from their query. Utilizing this benchmark enables the development of more accurate and robust NLU systems for Persian, contributing to improved conversational AI and other applications.

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