This is addressed in the original announcement post of SyntaxNet[0]:<p><i>The major source of errors at this point are examples such as the prepositional phrase attachment ambiguity described above, which require real world knowledge (e.g. that a street is not likely to be located in a car) and deep contextual reasoning. Machine learning (and in particular, neural networks) have made significant progress in resolving these ambiguities. But our work is still cut out for us: we would like to develop methods that can learn world knowledge and enable equal understanding of natural language across all languages and contexts.</i><p>The SyntaxNet team thinks that this is indeed a major source of errors and seems to be a focus of their work going forward.<p>[0] - <a href="http:&#x2F;&#x2F;googleresearch.blogspot.com&#x2F;2016&#x2F;05&#x2F;announcing-syntaxnet-worlds-most.html" rel="nofollow">http:&#x2F;&#x2F;googleresearch.blogspot.com&#x2F;2016&#x2F;05&#x2F;announcing-syntax...</a>