Inferencing, or machine reasoning has a slightly unsavoury reputation perhaps stemming from the failure of Strong AI and its association with science fiction. This is a bit unfortunate and it could be argued that it has led Semantic Web technologies to be underdeveloped.With the Semantic Web and RDF we are concerned with simple statements, or assertions. When humans make statements they generally rely on a large amount of background knowledge and contextual information to make their meaning clear without it being explicit. For example, if I say, “Mary had a little lamb,” it is unnecessary to explain that Mary is a person, Mary is female, a lamb is a young sheep, a sheep is a kind of quadrupedal animal or to digress in a discussion of what it means to “have” something, to what extent notions of ownership can extend to animals, or even the idea of time, past, present and future.
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It is nothing spectacular, just following chains of statements made by humans to answer questions that would be obvious to a two-year old. That said, this is just a toy example, the same principle can be used with facts and questions that are not quite so obvious. However, if the rules get much more complicated or numerous, it becomes quite a lot more computationally expensive to evaluate them.