TODO

• Tile paragraphs (http://www.nltk.org/api/nltk.tokenize.html#module-nltk.tokenize.texttiling)
• Tag paragraphs (location/crime) with NER (http://textminingonline.com/how-to-use-stanford-named-entity-recognizer-ner-in-python-nltk-and-other-programming-languages)
• sources: http://www.presseportal.de/polizeipresse/pm/43559/2758035/pol-gi-pressemeldung-vom-10-06-2014 and other stories

Dependencies

To run the code you need the following packages:

• Beautiful Soup 4
• unicodecsv

Acknowledgements

This work heavily relies on the Stanford Named Entity Tagger and the german models for it.

Problems

If you get errors like this:

LookupError: 
**********************************************************************
  Resource u'corpora/stopwords' not found.  Please use the NLTK
  Downloader to obtain the resource:  >>> nltk.download()
  Searched in:
    - '/Users/username/nltk_data'
    - '/usr/share/nltk_data'
    - '/usr/local/share/nltk_data'
    - '/usr/lib/nltk_data'
    - '/usr/local/lib/nltk_data'
**********************************************************************

You should run

>>> import ntlk
>>> nltk.download()

in the Python interpreter and download the resource described above.