title: Extracting Person Names from a text data in German Language using spacy or nltk?
body: <p>I am using a spacy model for german language for extracting named entities such as location names, person names and company names but not getting the proper result as an output. Is there any missing concept which I am unable to figure out precisely.</p>
  
  <pre><code>def city_finder(text_data):
      nlp = spacy.load('en_core_web_sm')
      doc = nlp(text_data)
      for ents in doc.ents:
          if(ents.label_ == 'GPE'):
              return (ents.text)
  </code></pre>
  
  <p>This is the code which I had used in order to find the city names from the text data but its accuracy is not very high. When I run this code the result is coming out to be something else instead of the city name. Is there something which I am missing out as part of the Natural Language Processing or any other area? </p>