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This chapter focuses on the methods for evaluating Natural Language Understanding (NLU) systems. It discusses the annotation of datasets and various performance assessment methods, covering different levels of understanding, from intent recognition to slot filling and domain classification.

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Evaluating 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 focuses on the methods for evaluating Natural Language Understanding (NLU) systems. It discusses the annotation of datasets and various performance assessment methods, covering different levels of understanding, from intent recognition to slot filling and domain classification.