Difference between revisions of "Natural Language Generation (NLG)"
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* [[Natural Language Processing (NLP)]] | * [[Natural Language Processing (NLP)]] | ||
* [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] | ||
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* Products | * 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] | ||
** [http://www.arria.com/nlg-studio-google-landing-a/ Arria] | ** [http://www.arria.com/nlg-studio-google-landing-a/ Arria] | ||
| − | ** [http://yseop.com/ | + | ** [http://yseop.com/ yseop] |
| + | ** [http://www.onlyboth.com/ OnlyBoth] | ||
| + | ** [http://www.textengine.io/en-gb/ textengine.io] | ||
| + | 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 has existed for a long time but commercial NLG technology has only recently become widely available. 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. [https://en.wikipedia.org/wiki/Natural-language_generation Wikipedia] | ||
http://narrativescience.com/wp-content/uploads/2018/11/graphic_Layers_Quill_1a_color2.png | http://narrativescience.com/wp-content/uploads/2018/11/graphic_Layers_Quill_1a_color2.png | ||
Revision as of 13:35, 23 February 2019
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- Natural Language Processing (NLP)
- Using Natural Language Processing for Smart Question Generation | Aditya S -Intel AI Academy
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 has existed for a long time but commercial NLG technology has only recently become widely available. 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
