33 lines
1.2 KiB
Python
33 lines
1.2 KiB
Python
import random
|
|
from typing import Dict
|
|
|
|
import pandas as pd
|
|
|
|
from processing.ner.formats import BaseNameFormatter
|
|
|
|
|
|
class ExtendedSurnameFormatter(BaseNameFormatter):
|
|
def transform(self, row: pd.Series) -> Dict:
|
|
native_parts = self.parse_native_components(row['probable_native'])
|
|
original_surname = row['probable_surname'] if pd.notna(row['probable_surname']) else ''
|
|
|
|
# Add random additional surname
|
|
additional_surname = random.choice(self.additional_surnames)
|
|
combined_surname = f"{additional_surname} {original_surname}".strip()
|
|
full_name = f"{row['probable_native']} {combined_surname}".strip()
|
|
|
|
return {
|
|
'name': full_name,
|
|
'probable_native': row['probable_native'],
|
|
'identify_name': row['probable_native'],
|
|
'probable_surname': combined_surname,
|
|
'identity_surname': combined_surname,
|
|
'ner_entities': str(self.create_ner_tags(full_name, native_parts, combined_surname)),
|
|
'transformation_type': self.transformation_type,
|
|
**self.compute_derived_attributes(full_name)
|
|
}
|
|
|
|
@property
|
|
def transformation_type(self) -> str:
|
|
return 'extended_surname'
|