Python Natural Language Processing
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Natural language understanding

Let's learn about natural language understanding:

  • Natural language understanding (NLU) is considered the first component of NLP
  • NLU is considered an Artificial Intelligence-Hard (AI-Hard) problem or Artificial Intelligence-Complete (AI-Complete) problem
  • NLU is considered an AI-Hard problem because we are trying to make a computer as intelligent as a human
  • NLU is hard, but nowadays, tech giants and research communities are improvising traditional Machine Learning algorithms and applying various types of deep neural network that will help to achieve the goal (computers can also have the intelligence to process natural language (NL))
  • NLU is defined as the process of converting NL input into useful a representation by using computational linguistics tools
  • NLU requires the following analysis to convert NL into a useful representation:
    • Morphological analysis
    • Lexical analysis
    • Syntactic analysis
    • Semantic analysis
    • Handling ambiguity
    • Discourse integration
    • Pragmatic analysis

In this book, we will focus on NLU and develop an NLP-based system that uses NLU representation.