Natural Language Generation (NLG)

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• Natural Language Processing (NLP)
• The Future of Writing, With Robots | Garrett Grams
• Using Natural Language Processing for Smart Question Generation | Aditya S -Intel AI Academy
• Neural text generation: How to generate text using conditional language models | Neil Yager
• Narrative Science Systems: A Review | P. Sarao, P. Mittal, R. Kaur
• Generative Pre-trained Transformer-2 (GPT-2)
• NLP for Analytics: It's Not Just About Text | Lisa Morgan - InformationWeek

• Companies:
  • Narrative Science Quill
  • Automated Insights Wordsmith
  • Arria
  • yseop
  • Digital Reasoning
  • Abodit Natural Language Engine for .NET
  • PhraseTech
  • textengine.io
  • OnlyBoth
  • Linguastat
  • Retresco
  • AX Semantics
  • Syllabs
  • Labsense
  • Textio augmented writing

Natural-language generation (NLG) is the natural-language processing task of generating natural language from a machine-representation system such as a knowledge base or a logical form. Psycholinguists prefer the term language production when such formal representations are interpreted as models for mental representations. It could be said an NLG system is like a translator that converts data into a natural-language representation. However, the methods to produce the final language are different from those of a compiler due to the inherent expressivity of natural languages. ...NLG may be viewed as the opposite of natural-language understanding: whereas in natural-language understanding, the system needs to disambiguate the input sentence to produce the machine representation language, in NLG the system needs to make decisions about how to put a concept into words. Wikipedia

Mapping the Field of Algorithmic Journalism | Konstantin N. Dörr

• Artificial intelligence in healthcare: an interview with Dr Ehud Reiter | News Medical Life Sciences
• Arria NLG Engine