How about looking at it this way. We now have multiple implementations that get 94%+ success _without_ knowing anything about the world. Isn&#x27;t that remarkable?<p>Now to get to 99.4%+ how about we combine techniques such as spaCy or Parsey McParseFace (love the name Google) with very simple real-world cognitive models. So for the example given &quot;Alice drove down the street in her car.&quot; a simple cognitive model would _know_ that streets cannot be in cars and so be able to disambiguate. A cognitive model wouldn&#x27;t know all the facts about the world, it would know certain things about streets, certain things about cars and be able to infer on the fly whether the relationship between streets and cars matches either the first parse possibility or the second. To me this seems like the obvious next step. If it&#x27;s obvious to me it must have been obvious to someone else so presumably somebody is working on it.