30 lines
1.0 KiB
Python
30 lines
1.0 KiB
Python
from typing import Dict
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import pandas as pd
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from processing.ner.formats import BaseNameFormatter
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class PositionFlippedFormatter(BaseNameFormatter):
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def transform(self, row: pd.Series) -> Dict:
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native_parts = self.parse_native_components(row['probable_native'])
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surname = row['probable_surname'] if pd.notna(row['probable_surname']) else ''
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# Flip order: surname + native components
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full_name = f"{surname} {row['probable_native']}".strip()
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return {
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'name': full_name,
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'probable_native': row['probable_native'],
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'identify_name': row['probable_native'],
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'probable_surname': surname,
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'identify_surname': surname,
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'ner_entities': str(self.create_ner_tags(full_name, native_parts, surname)),
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'transformation_type': self.transformation_type,
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**self.compute_derived_attributes(full_name)
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}
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@property
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def transformation_type(self) -> str:
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return 'position_flipped'
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