| import json |
| import jsonlines |
| import argparse |
| import pandas as pd |
| import pprint |
|
|
| def main(args): |
| mainDict = {} |
| with jsonlines.open(args.input_file) as reader: |
| for obj in reader: |
| |
| neutral = "" |
| entailment = "" |
| contradiction = "" |
| prompt = "" |
|
|
| if mainDict.get(obj['promptID'], None): |
| prompt = obj['sentence1'] |
| entailment = mainDict[obj['promptID']].get('entailment','') |
| contradiction = mainDict[obj['promptID']].get('contradiction','') |
| neutral = mainDict[obj['promptID']].get('neutral','') |
|
|
| if obj['gold_label'] == "neutral": |
| neutral = obj['sentence2'] |
| elif obj['gold_label'] == "contradiction": |
| contradiction = obj['sentence2'] |
| elif obj['gold_label'] == "entailment": |
| entailment = obj['sentence2'] |
| |
| mainDict[obj['promptID']] = {'prompt': prompt, 'entailment' : entailment, 'neutral' : neutral, 'contradiction' : contradiction} |
| |
| myList = [] |
| for promptID in mainDict: |
| myList.append({'sent0':mainDict[promptID]['prompt'], 'sent1':mainDict[promptID]['entailment'], 'hard_neg':mainDict[promptID]['contradiction']}) |
| |
| df = pd.DataFrame.from_records(myList) |
| |
| |
| df.replace("", float("NaN"), inplace=True) |
| df.dropna(subset = ["sent0","sent1","hard_neg"], inplace=True) |
| |
| |
| df.to_csv(args.output_file, index=False) |
|
|
| if __name__ == '__main__': |
| parser = argparse.ArgumentParser() |
| parser.add_argument('--input_file', help="Input file.", required=True) |
| parser.add_argument('--output_file', help="Output file.", required=True) |
| |
| args = parser.parse_args() |
| main(args) |
|
|
