eshijia / insurance_qa_python

Python-formatted InsuranceQA data

insurance_qa_python

About

Insurance QA data formatted as Python objects and pickled.

Example usage

Clone locally

git clone https://github.com/codekansas/insurance_qa_python.git
cd insurance_qa_python
pwd # where files are stored

Load a file in Python

import pickle

def load(file_name):
  return pickle.load(open(os.path.join(path, file_name), 'rb'))

About files:

• vocabulary: dict object of (word index <int> -> word <str>) relationships
• answers: dict object of (answer index <int> -> word indices <list of ints>) relationships
• train: list of dict (one dict per entry), where each dict has:
  • question: the word indices for the question
  • answers: the answer indices for each of the question's ground truth
• dev / test1 / test2: list of dict (one dict per entry), where each dict has:
  • question: the word indices for the question
  • good: the ground truth
  • bad: the other answers from the dataset

Resources

• Original Github page
• arXiv paper

Cite

Applying Deep Learning to Answer Selection: A Study and An Open Task
Minwei Feng, Bing Xiang, Michael R. Glass, Lidan Wang, Bowen Zhou ASRU 2015