/neural-question-generation

pytorch implmentation of Paragraph-level Neural Question Generation with Maxout Pointer and Gated Self-attention Networks

Primary LanguagePythonMIT LicenseMIT

Neural Question Generation

This is not official implementation from the paper Paragraph-level Neural Question Generation with Maxout Pointer and Gated Self-attention Networks I implemented in Pytorch to reproduce similar result as the paper

Dependencies

This code is written in Python. Dependencies include

Download data and Preprocess

mkdir squad
wget http://nlp.stanford.edu/data/glove.840B.300d.zip -O ./data/glove.840B.300d.zip 
unzip ./data/glove.840B.300d.zip 
wget https://rajpurkar.github.io/SQuAD-explorer/dataset/train-v1.1.json -O ./squad/train-v1.1.json
wget https://rajpurkar.github.io/SQuAD-explorer/dataset/dev-v1.1.json -O ./squad/dev-v1.1.json
cd data
python process_data.py

Configuration

You might need to change configuration in config.py.
If you want to train, change train = True and set gpu device in config.py

Evaluation from this repository

cd qgevalcap
python2 eval.py --out_file prediction_file --src_file src_file --tgt_file target_file

Results

BLEU_1 BLEU_2 BLEU_3 BLEU_4
44.57 29.34 21.74 16.28