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Narwhal is a keyword and key NARRATIVE manager that creates text aware classes. This is simple Natural Language Understanding (NLU) without Natural Language Processing (NLP). Narhwal is a geometric, rather than statistical approach to language. It embeds detailed topic knowledge which is called "narrow world language processing". The concept of …

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  • See "QuickStart.txt" for tutorial sketch

  • See "examples" and "narhwal_noise" for more complete examples of Narwhal applications.

  • See DOCS for Narwhal specification, hints for debugging, etc.

  • See "nwchat.py" for chat template (under development)

Narwhal is a library of objects that can read text. It uses keywords based on client-provided synonym lists and also client-provided formulas in the keywords. So the client can focus on the details of the topic vocabularies and how people express themselves, rather than on how language works. While relying on Narwhal to understand the incoming language the client must still write code that transfers information from the Narwhal objects into more convenient data structures.

The Narwhal approach is to embed detailed topic knowledge. This is called "narrow world language processing". Here, the "narrow world" of the client's topics is essentially the same thing as a semantic "frame” as described by Fillmore and archived at Berkeley's FrameNet.

Inquiries are welcome.

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Narwhal is a keyword and key NARRATIVE manager that creates text aware classes. This is simple Natural Language Understanding (NLU) without Natural Language Processing (NLP). Narhwal is a geometric, rather than statistical approach to language. It embeds detailed topic knowledge which is called "narrow world language processing". The concept of …

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