Credit to Volley (http://volley.com) for requesting/inspiring this project!
requirements.txt contains the libraries/modules you'll need (It's come to my attention that the Wikipedia library has a bug, so I recommend this instead: http://stackoverflow.com/questions/34869597/wikipedia-api-for-python#35122688). You'll also need to download some data so that the nltk library works. To do this, start the Python console (ie. type python on the command line) and then:
>>> import nltk
>>> nltk.download('averaged_perceptron_tagger')
>>> nltk.download('punkt')
Run server.py to get the Flask endpoints working, and then open up index.html - that's all!
Choosing more appropriate multiple-choice options, especially for numbers
ie. if the answer is '1960s', show '1950s' as another option.
Ignoring the less text heavy parts of a Wikipedia page.
Creating more interesting grammar for the text chunker, which would lead to more interesting question types.
Some of the questions presented currently lack context about what the question is referring to. A further version of this project would attempt to interpret the context of the sentence in question and include that in the question.
ie. references to 'they' or 'he' would be replaced by what those pronouns are actually referring to.