Named Entity Recognition using SpaCy in 5 minutes

Recently, I am looking it SpaCy, a startup and an NLP toolkit. It is fabulous on its speed. Today, I just gave it a try on NER. Just a few lines (as in iPython):

In [1]: import spacy.en
In [2]: parser = spacy.en.English()
In [12]: ParsedSentence = parser(u"alphabet is a new startup specializing in eating their own words on leaving china to fight for information freedom")

In [13]: print ParsedSentence.ents
()

In [14]: ParsedSentence = parser(u"Alphabet is a new startup specializing in eating their own words on leaving China to fight for information freedom")

In [15]: print ParsedSentence.ents
(Alphabet, China)

In [16]: for Entity in  ParsedSentence.ents:    
   ....:     print Entity.label, Entity.label_, ' '.join(t.orth_ for t in Entity)
   ....:     
349 ORG Alphabet
350 GPE China

I used only default settings. Apparently, the NER of SpaCy is very sensitive to case of words.