We are on the cusp of solving natural language understanding, which will enable natural language for humans and relational databases for computers. There will be no "Semantic Web", there will the "Web" and the machines that read it just as well as humans.
I think we are still very far away from NLU. There are a couple of tiny subproblems such as Entity Extraction, Relation Extraction and Dependency Parsing that we have become pretty good at (for English that is, but for many languages even that is still difficult). However, once you get into pragmatics and contextual understanding we still have no clue. And in order to enable real NLU you'd also need to ability to do reasoning on top of other knowledge (and "common sense"), which is a whole different problem.
Based on products like Siri or Cortana it may seem like we are coming closer to NLU, but the reason those are working at all is because they are very topic-specific and tiny subproblems of what NLU is really about.
Except that sadly, the only machines that will read it will have to be centralised in the hands of cloud providers in order to provide the funding and power needed to run them.
One of the great things about the semantic web, to me, was always that you could process it on a cheap VPS or your own desktop, creating new systems with little or no knowledge of math or machine learning. (I know projects that do this today.) That's not going to happen for a long time with natural language processing.
>>We are on the cusp of solving natural language understanding
Why do you think this? Is it just a feel or is there some company that is really close. As another user mentioned in this thread natural language understanding seems to be the same thing as solving strong AI. Solving strong AI is a huge deal. So big that the people in control of it will probably become the most powerful people in the world.
Whether we are on the cusp really depends on what we mean by "natural language understanding" specifically. What about Watson? It seems to "understand" quite a bit of natural language just fine and can answer interesting questions posed in same. If that doesn't count as "understanding", I'd like to know what does? It probably can't do extended reasoning based on its "understanding", but that would seem to me to be moving the goal posts.
I doubt that a sufficiently well-defined notion of natural language understanding that does not specifically include strong artificial intelligence in its definition would require strong AI. Constructing such a definition is left as an exercise to the reader.
Thinking that strong AI is required for natural language understanding may end up being similar to how it was once thought that beating humans at chess would require advanced AI. Brute forse can do wonderful things, as can weak AI.
Natural language understanding is typically regarded as AI-complete, and once we have that, semantic web will be the least interesting bit of new technology.
