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This chapter looks at single-turn NLU, focusing on tasks that involve interpreting and processing user inputs in a single interaction. It covers essential tasks like intent classification and slot filling, exploring both traditional and modern machine learning approaches. It also examines the role of external resources and key datasets in enhancing NLU systems.

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Single-Turn Natural Language Understanding

  • 章节

  • 发表日期：

    2025年

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  • Soyeon Caren Han,
  • Henry Weld,
  • Yan Li,
  • Jean Lee,
  • Josiah Poon

摘要

This chapter looks at single-turn NLU, focusing on tasks that involve interpreting and processing user inputs in a single interaction. It covers essential tasks like intent classification and slot filling, exploring both traditional and modern machine learning approaches. It also examines the role of external resources and key datasets in enhancing NLU systems.