gradio-LegalNER / src /convertTotext.py
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def convertTotext(data_token, prediction_label):
prev_tag = 'O'
result = {}
temp = ''
for i, word in enumerate(data_token):
if prediction_label[i] != 'O':
if prev_tag == 'O' and temp != '':
temp = ''
if '##' in word:
temp += word.replace('##', '')
else:
temp += ' ' + word
else:
if temp != "":
result[prev_tag.replace("I_", "B_")] = temp.strip()
temp = ""
prev_tag = prediction_label[i]
return result