Datasets:
GEM
/

Tasks:
Other
Languages:
English
Multilinguality:
unknown
Size Categories:
unknown
Language Creators:
unknown
Annotations Creators:
crowd-sourced
Source Datasets:
original
ArXiv:
Tags:
question-generation
License:
squad_v2 / data_preparation.py
Abinaya Mahendiran
Updated train/test split
9352866
""" Script to prepare the SQuAD2.0 data to the GEM format
@author: AbinayaM02
"""
# Import libraries
import json
import pandas as pd
from sklearn.model_selection import train_test_split
# Function to generate gem id
def add_gem_id(data: dict, split: str) -> dict:
"""
Add gem id for each of the datapoint in the dataset.
Parameters:
-----------
data: dict,
data.
split: str,
split of data (train, test or validation).
Returns:
--------
dict
dictionary with updated id
"""
gem_id = -1
generated_data = {"data": []}
id_list =[]
for example in data:
title = example["title"]
for paragraph in example["paragraphs"]:
context = paragraph["context"] # do not strip leading blank spaces GH-2585
for qa in paragraph["qas"]:
temp_dict = {}
question = qa["question"]
qa_id = qa["id"]
answer_starts = [answer["answer_start"] for answer in qa["answers"]]
answers = [answer["text"] for answer in qa["answers"]]
# Features currently used are "context", "question", and "answers".
# Others are extracted here for the ease of future expansions.
gem_id += 1
temp_dict["id"] = qa_id
temp_dict["gem_id"] = f"gem-squad_v2-{split}-{gem_id}"
temp_dict["title"] = title
temp_dict["context"] = context
temp_dict["question"] = question
temp_dict["answers"] = {
"answer_start": answer_starts,
"text": answers,
}
generated_data["data"].append(temp_dict)
return generated_data
# Function to split data
def split_data(file_name: str, data_type: str) -> (dict, dict):
"""
Method to split the data specific to SQuAD2.0
Parameters:
-----------
file_name: str,
name of the file.
data_type: str,
type of the data file.
Returns:
--------
(dict, dict)
split of data
"""
if data_type == "json":
with open(file_name, 'r') as json_file:
data = json.load(json_file)["data"]
json_file.close()
# split the data into train and test
# 90% train data 10% test data
train, test = train_test_split(data, train_size=0.9, random_state = 42)
return(train, test)
# Function to save json file
def save_json(data: dict, file_name: str):
"""
Method to save the json file.
Parameters:
----------
data: dict,
data to be saved in file.
file_name: str,
name of the file.
Returns:
--------
None
"""
# save the split
with open(file_name, "w") as data_file:
json.dump(data, data_file, indent = 2)
data_file.close()
if __name__ == "__main__":
# split the train data
train, test = split_data("squad_data/train-v2.0.json", "json")
# add gem id to train split
train = add_gem_id(train, "train")
# save the train split
save_json(train, "train.json")
# add gem id to test split
test = add_gem_id(test, "test")
# save the test split
save_json(test, "test.json")
# load validation data
with open("squad_data/dev-v2.0.json", "r") as dev_file:
validation = json.load(dev_file)["data"]
dev_file.close()
# add gem id and save valid.json
validation = add_gem_id(validation, "validation")
save_json(validation, "validation.json")