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import json
import argparse
def create_entailment_data(train_data):
entailment_data = [d for d in train_data if len(d['evidence']) > 0]
# entailment data
for d in entailment_data:
entailment_answer = d['answer'].lower()
if d['answer'].lower() not in ['yes', 'no']:
entailment_answer = 'maybe'
if len(d['history']) > 0:
# this means that not all the information needed to get to the answer were provided in the scenario
# (they were provided in the history). Therefore the entailment label should be 'maybe'
entailment_answer = 'maybe'
d['entailment_answer'] = entailment_answer
entailment_path = 'train_entailment_sharc.json'
with open(entailment_path, 'w') as f:
f.write(json.dumps(entailment_data, indent=True))
print('Wrote ShARC entailment data to ' + entailment_path)
return entailment_data
def filter_train_data(sharc_train_path, sharc_dev_path):
sharc_train_data = json.load(open(sharc_train_path))
sharc_dev_data = json.load(open(sharc_dev_path))
sharc_data = sharc_train_data + sharc_dev_data
train_utterance_ids = open('train_utterance_ids.txt').read().splitlines()
train_data = [d for d in sharc_data if d['utterance_id'] in train_utterance_ids]
return train_data
def create_qa_data(entailment_data):
qa_data = []
for d in entailment_data:
for e in d['evidence']:
q_key = 'follow_up_question'
a_key = 'follow_up_answer'
if 'follow_up_question' in e:
qa_data.append({
'utterance_id': d['utterance_id'],
'context': d['scenario'],
'question': e[q_key],
'answer': e[a_key].lower()
})
for h in d['history']:
qa_data.append({
'utterance_id': d['utterance_id'],
'context': d['scenario'],
'question': h['follow_up_question'],
'answer': 'maybe'
})
if d['answer'].lower() not in ['yes', 'no']:
qa_data.append({
'utterance_id': d['utterance_id'],
'context': d['scenario'],
'question': d['answer'],
'answer': 'maybe'
})
qa_path = 'train_qa_sharc.json'
with open(qa_path, 'w') as f:
f.write(json.dumps(entailment_data, indent=True))
print('Wrote ShARC QA data to ' + qa_path)
return qa_data
if __name__ == '__main__':
parser = argparse.ArgumentParser('Script for generating entailment and QA data from ShARC for training')
parser.add_argument('-sharc_train_path', type=str, default='sharc_train.json', help='path to ShARC train file')
parser.add_argument('-sharc_dev_path', type=str, default='sharc_dev.json', help='path to ShARC dev file')
args = parser.parse_args()
sharc_train_path = args.sharc_train_path
sharc_dev_path = args.sharc_dev_path
train_data = filter_train_data(sharc_train_path, sharc_dev_path)
entailment_data = create_entailment_data(train_data)
qa_data = create_qa_data(entailment_data)
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