Knowledge technology is based on applying smart algorithms to keywords, by which the natural meaning of non-keywords is ignored.
Non-keywords provide information to our brain about the structure of the sentence. However, scientists have not discovered the natural meaning of non-keywords yet. Thinknowlogy is the world's only knowledge technology that implements the self-organizing function of non-keywords. I defy anyone to beat my natural language reasoner.
Thinknowlogy is open source, for the benefit of all
Thinknowlogy is experimental, grammar-based software,
designed to utilize Natural Laws of Intelligence in grammar,
in order to create intelligence – through natural language – in software,
which is demonstrated by:
• Programming in natural language;
• Reasoning in natural language:
• drawing conclusions (more advanced than scientific solutions),
• making assumptions (with self-adjusting level of uncertainty),
• asking questions (about gaps in the knowledge),
• detecting conflicts and some cases of semantic ambiguity;
• Multilingualism, proving: Natural languages have one common origin.
According to the evolution theory, intelligence and language would have evolved independently of each other. So, the evolution theory doesn't support a systematic relationship between reasoning and language, while the biblical world view assumes that reasoning and language are closely related. Being based on the biblical world view, Thinknowlogy is the only reasoner able to process the natural meaning of words like definite article “the”, conjunction “or”, possessive verb “has / have” and past tense verbs “was / were” and “had”. It has worldwide unique results:
• Reasoning in natural language, expressing its reasoning output in readable sentences;
• Preserving the meaning throughout the system;
• Autonomous structuring of its knowledge base, while IBM's Watson needs raw processing power "to find a needle in the haystack of unstructured texts" (quote from IBM);
• Detecting some cases of semantic ambiguity: Disambiguation is considered the biggest problem in knowledge technology. Detecting semantic ambiguity is my first step towards a fundamental solution. Later I will implement autonomous semantic disambiguation.