On the other hand, we suspect that Google's embeddings perform poorly because of vocabulary mismatch -in particular, Google's embeddings were trained in a case-sensitive manner, and embeddings for many common punctuations and 27 Wilcoxon rank sum test, p < 0.001 28 To make a direct comparison to<cite> Collobert et al. (2011b)</cite> , we do not exclude the CoNLL-2003 NER task test data from the word vector training data.