Datasets:
Multilinguality:
multilingual
Size Categories:
100K<n<1M
Annotations Creators:
expert-generated
License:
import json | |
import jsonlines | |
import argparse | |
import pandas as pd | |
import pprint | |
from random import * | |
def main(args): | |
mainDict = {} | |
with jsonlines.open(args.norwegian_input_file) as reader: | |
for obj in reader: | |
#Check if the value already exists | |
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) | |
#Drop empty | |
df.replace("", float("NaN"), inplace=True) | |
df.dropna(subset = ["sent0","sent1","hard_neg"], inplace=True) | |
#Get the english file | |
english = pd.read_csv(args.english_input_file) | |
#Get the multilingual lookup file | |
multi = pd.read_csv(args.multilingual_input_file, sep='\t') | |
multi.columns=['id','english','norwegian'] | |
multi['english'] = multi['english'].str.strip() | |
multi['norwegian'] = multi['norwegian'].str.strip() | |
#Create dictionary | |
mydict = {} | |
for index,row in multi.iterrows(): | |
mydict[row['norwegian']] = row['english'] | |
merged = df.copy() | |
for index, row in merged.iterrows(): | |
flip = randint(1,6) | |
if flip == 3 or flip == 4 or flip == 5: | |
merged.at[index, 'sent0'] = mydict.get(row['sent0'],row['sent0']) | |
if flip == 2 or flip == 4 or flip == 6: | |
merged.at[index, 'sent1'] = mydict.get(row['sent1'],row['sent1']) | |
if flip == 1 or flip == 5 or flip == 6: | |
merged.at[index,'hard_neg'] = mydict.get(row['hard_neg'],row['hard_neg']) | |
combined = pd.concat([df, english, merged]) | |
combined = combined.sample(frac=1).reset_index(drop=True) | |
#Save csv | |
combined.to_csv(args.output_file, index=False) | |
if __name__ == '__main__': | |
parser = argparse.ArgumentParser() | |
parser.add_argument('--norwegian_input_file', help="Norwegian json file.", required=True) | |
parser.add_argument('--english_input_file', help="English csv file.", required=True) | |
parser.add_argument('--multilingual_input_file', help="Multilingual tsv file.", required=True) | |
parser.add_argument('--output_file', help="Output file.", required=True) | |
args = parser.parse_args() | |
main(args) | |