RACE Reading Comprehension Task

Code for the paper: RACE: Large-scale ReAding Comprehension Dataset From Examination. Guokun Lai*, Qizhe Xie*, Hanxiao Liu, Yiming Yang and Eduard Hovy. EMNLP 2017

Leaderboard of RACE

Dependencies

• Python 2.7
• Theano >= 0.7
• Lasagne 0.2.dev1

Datasets

• RACE: Please submit a data request here. The data will be automatically sent to you. Create a "data" directory alongside "src" directory and download the data.

• Word embeddings:

  • glove.6B.zip: http://nlp.stanford.edu/data/glove.6B.zip

Usage

Preprocessing

* python preprocess.py

Stanford AR

* test pre-trained model: bash test_SAR.sh
* train: bash train_SAR.sh (The pre-trained model will be replaced)

GA

* test pre-trained model: bash test_GA.sh
* train: bash train_GA.sh (The pre-trained model will be replaced)

Reference

@inproceedings{lai2017large,
  title={RACE: Large-scale ReAding Comprehension Dataset From Examinations},
  author={Lai, Guokun and Xie, Qizhe and Liu, Hanxiao and Yang, Yiming and Hovy, Eduard},
  booktitle={EMNLP},
  year={2017}
}

Acknowledgement

• The code is adapted from Stanford AR https://github.com/danqi/rc-cnn-dailymail and GA https://github.com/bdhingra/ga-reader

Contact

• Please contact Qizhe Xie (qzxie AT cs DOT cmu DOT edu) if you find bugs or missing info

License

MIT