Difference between revisions of "Natural Language Generation (NLG)"

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* [http://software.intel.com/en-us/articles/using-natural-language-processing-for-smart-question-generation Using Natural Language Processing for Smart Question Generation | Aditya S -Intel AI Academy]
 
* [http://software.intel.com/en-us/articles/using-natural-language-processing-for-smart-question-generation Using Natural Language Processing for Smart Question Generation | Aditya S -Intel AI Academy]
 
* [http://medium.com/phrasee/neural-text-generation-generating-text-using-conditional-language-models-a37b69c7cd4b Neural text generation: How to generate text using conditional language models | Neil Yager]
 
* [http://medium.com/phrasee/neural-text-generation-generating-text-using-conditional-language-models-a37b69c7cd4b Neural text generation: How to generate text using conditional language models | Neil Yager]
* [http://arxiv.org/pdf/1902.04094.pdf BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model | Alex Wang, Kyunghyun Cho]
 
  
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* Products:
 
** [http://narrativescience.com/what-is-nlg/ Narrative Science]  
 
** [http://narrativescience.com/what-is-nlg/ Narrative Science]  
 
** [http://automatedinsights.com/ Automated Insights]
 
** [http://automatedinsights.com/ Automated Insights]

Revision as of 20:04, 23 February 2019

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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


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