37 lines
1.3 KiB
Python
37 lines
1.3 KiB
Python
import random
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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 ConnectorFormatter(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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connector = random.choice(self.connectors)
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# Connect native parts with a random connector
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if len(native_parts) > 1:
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connected_native = f" {connector} ".join(native_parts)
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full_name = f"{connected_native} {surname}".strip()
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else:
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connected_native = f"{row['probable_native']} {connector} {row['probable_native']}".strip()
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full_name = f"{connected_native} {surname}".strip()
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return {
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'name': full_name,
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'probable_native': connected_native,
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'identify_name': connected_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 'connector_added'
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