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Reviewed commit: ff1668a3f4
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| if term and term in question: | ||
| match = match_alias_to_column(term, columns, concepts) | ||
| mappings.append(match) | ||
| if match.status == "success" and match.matched_column: | ||
| normalized_question = normalized_question.replace(term, match.matched_column) |
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Replace only whole entity tokens during normalization
normalize_question_entities matches aliases with plain substring checks and then runs global str.replace, so terms that appear inside longer words are rewritten incorrectly. For example, with column 시군구명 and question 시군구명 별 ..., the canonical term 시군구 matches and replacement produces 시군구명명 ..., which then feeds a corrupted question into the prompt. This can silently degrade analysis whenever a concept term is a prefix/subsequence of another token.
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