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I wanted to create a question answerer for Wikipedia articles. This project reads articles and responds to a set of questions, getting 31% accuracy on the test set of questions
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This is my question-answering project for Information Extraction This folder contains the source code that I wrote, as well as the datasets I used, but it leverages a few different external libraries, as documented in my technical design --MY SOURCE CODE-- /helpers - This is a Python module I created with helper functions required to support question answering. These helpers could be anything from reading a file to searching for RegEx matches to finding the Jaccard similarity of two sentences /questionAnswering - This is the Python module with the Question Answering algorithm I used. As mentioned above, I tried to encapsulate any methods/information non-essential to the algorithm inside the /helpers module and use it here test.py - Script to actually run the test for the accuracy of the question-answerer --DATASETS-- /datasets /train - Two datasets used in development (S08 and S09) /test - One dataset used only for testing (S10) --RUNNING THE PROGRAM-- At runtime, the script fetches those libraries and uses them in the algorithm To run the program with the development sets, type the following command into a CADE lab Linux terminal: sh qa.sh To run the program with the test set, type the following command into a CADE lab Linux terminal: sh full.sh I have tested to be sure that permissions are open for the necessary folders.