Automated Language Generation (NLG) Task

An Automated Language Generation (NLG) Task is a language processing task that involves automatically producing natural language expressions, primarily text items, using computational methods.

• Context:
  • Output: NLG Task Output (Machine Written text)
  • Performance Measure: NLG Performance Measure, such as Syntactic Correctness and Intelligibility
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  • It can range from being a Domain-Specific NLG Task to being an Open-Domain NLG Task, based on topic breadth
  • It can range from being a Word Generation Task to being a Document Generation Task, based on linguistic unit size
  • It can range from being a Freeform NLG Task to being a Topic-based NLG Task, based on topical constraint
  • It can range from being a Shallow NLG Task to being a Deep NLG Task, based on linguistic processing depth
  • It can range from being a Short-form NLG Task to being a Long-form NLG Task, based on text length
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  • It can be solved by an Automated Language Generation System (that implements an NLG algorithm)
  • It can be supported by a Natural Language Understanding Task
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• Example(s):
  • NLG Task Types by Linguistic Depth:
    • Shallow NLG Tasks, such as: Automated Tweet Writing and Automated Text Error Correction
    • Deep NLG Tasks, such as: Automated Contract Redline Summarization
  • NLG Task Types by Text Length:
    • Short-form NLG Tasks, such as Automated Tweet Writing, ...
      • Automated Definitional Sentence Generation
      • Automated Image Description Generation
    • Long-form NLG Tasks:
      • Automated Wikitext Generation (wikitext generation), such as Automated Wikipedia Page Creation
      • Automated Essay Writing
  • NLG Task Types by Domain Specificity:
    • Domain-Specific NLG Tasks, such as: Medical NLG and Legal NLG
    • Open-Domain NLG Tasks, such as: Automated Question Answering or Automated Summarization
  • NLG Task Types by Linguistic Unit:
    • Word Generation Tasks, such as: Automated Synonym Generation
    • Phrase Generation Tasks, such as: Automated Paraphrasing
    • Sentence Generation Tasks, such as: Automated Definitional Sentence Generation and Automated Image Description Generation
    • Passage Generation Tasks, such as: Automated Summarization, such as contract summarization
    • Document Generation Tasks, such as Automated Wikipedia Page Creation or Automated Contract Drafting
  • NLG Task Types by Topical Constraint:
    • Freeform NLG Tasks, such as: CJS Neural Narrative Text Generation Task
    • Automated Domain-Specific NLG, such as Medical NLG, Legal NLG, Software NLG
    • Constrainted NLG Task, such as: Generate Text(length={200}, subject='history', vocabulary='advanced', tone='formal', structure='intro, body, conclusion', deadline='2023-12-31', sentiments='neutral', audience='adults') => "Introduction about the subject of history. Detailed body text employing an advanced vocabulary and a formal tone. Conclusive remarks. Completed before the specified deadline, aimed at an adult audience with a neutral sentiment."
  • Writing Assistance Tasks, such as: ...
  • Data-to-Text Generation Task, such as: Data-to-Text Generation via Template-based Design.
  • Machine Translation Task.
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• Counter-Example(s):
  • an Automated Natural Language Understanding (NLU) Task.
  • Human-Performed Language Generation Task, such as Human-Performed Writing.
  • Automated Software Programming.
  • Automated Speech Generation.
  • Autoamted Image Generation.
• See: Automated Text Generation (NLG) Task, Automated Written Language Generation Task, Natural Language Generation Task, Content Planning, Document Structuring, Lexical Choice, Narrative Generation, Pragmatic Analysis, Semantic Analysis, Surface Realization, Text Planning, Text Structuring.

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