Learning to generate questions from text.
Blog on this project :
Link1 : https://software.intel.com/en-us/articles/using-natural-language-processing-for-smart-question-generation
Link2 : http://dynamichub.in/aditya/sqg/
Some details about the project has also been mentioned in procedure.txt file which lies in the home directory itself.
Install Python2.7`in your system
git clone https://github.com/adityasarvaiya/Automatic_Question_Generation.git
cd Automatic_Question_Generation
pip install -r requirements.txt
if you have problem with dotenv package then uninstall dotenv and install python-dotenv
pip install nltk
python
import nltk
nltk.download("punkt")
nltk.download("stopwords")
nltk.download("averaged_perceptron_taggepython r")
mkdir /your-path-to-stanford-models/stanford-models
.stanford-parser.jar
to stanford models folder, e.g. /your-path-to-stanford-models/stanford-models/stanford-parser.jar
stanford-parser-x-x-x-models.jar
to stanford models folder.stanford-parser-x-x-x-models.jar
, move /edu/stanford/nlp/models/lexparser/englishPCFG.ser.gz
to stanford-models/
stanford-ner.jar
to stanford models folder.stanford-ner-x-x-x.jar
to stanford models folder (e.g. 3.7.0)./classifiers/english.all.3class.distsim.crf.ser.gz
to stanford models folder.The stanford models folder should looks like this:
- stanford-models/
| - stanford-parser.jar
| - stanford-parser-x-x-x-models.jar
| - englishPCFG.ser.gz
| - stanford-ner.jar
| - stanford-ner-x-x-x.jar
| - english.all.3class.distsim.crf.ser.gz
Create environment variable file with: touch .env
for configuration (in project root).
SENTENCE_RATIO = 0.05 #The threshold of important sentences
STANFORD_JARS=/path-to-your-stanford-models/stanford-models/
STANFORD_PARSER_CLASSPATH=/path-to-your-stanford-models/stanford-models/stanford-parser-x.x.x-models.jar
STANFORD_NER_CLASSPATH=/path-to-your-stanford-models/stanford-models/stanford-ner.jar
ID | Variable Name | Variable Location | USE |
---|---|---|---|
1 | SENTENCE_RATIO | .env file | Controls the ratio to sentence selection from given text. Range [0,1] |
2 | len(entities) > 7 | aqg/utils/gap_selection line 58 | It elemenates any sentence with more than 7 entities |
[embed] https://github.com/adityasarvaiya/Automatic_Question_Generation/blob/master/project.pdf [/embed]