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Generating Questions and Multiple-Choice Answers using Semantic Analysis of Texts

This repository provides source code used for the COLING 2016 paper titled ``Generating Questions and Multiple-Choice Answers using Semantic Analysis of Texts.'' It contains code for two question algorithms (QG1 and QG2) and distractor generation.

Requirements

  • Python 3.6 (for QG1 only)
  • Python 2.7
  • Java 8 (for preprocessing)

For other requirements on python packages, please look at requirements.txt.

How to Run the Code

$ preprocess.sh
$ run.sh

Citation

If you use the source code, please cite our COLING 2016 paper:

@inproceedings{Araki2016Generating,
  author    = {Jun Araki and Dheeraj Rajagopal and Sreecharan Sankaranarayanan and Susan Holm and Yukari Yamakawa and Teruko Mitamura},
  title     = {Generating Questions and Multiple-Choice Answers using Semantic Analysis of Texts},
  booktitle = {Proceedings of COLING},
  pages     = {1125--1136},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
}