fix(site): drive school/program naming from manual authority tables, … - #7
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…drop fuzzy matching 升学站「相同院校专业合并」与「最终去向(Q9)绑定」此前依赖 signature_tokens 特征词 + 同校单Admit/token重合等模糊启发式, 会把项目拆成碎片、把去向误绑到被拒项目 (如 CRN 去向被绑到其被拒的 NUS Supply Chain Management)。 改为人工逐人编纂的确定性权威表, 代码只做精确查表, 删除全部模糊逻辑: - program_aliases.csv: (raw_school, raw_project) → canonical 全名。correct.xlsx 的 C 列逐字优先; 其余按人工判断/核实写定。canonical 即 program identity 与展示名, 相同 canonical → 同一节点(正确合并, 无碎片)。 - destination.csv: user_id → chosen_canonical。逐人读 q9 + admit 列表后人工判定; 运行时只做 canonical 全等绑定, 命中标 Chosen, 否则独立 Chosen, 绝不碰 reject。 - normalize.py: 删 signature_tokens; ProgramNormalizer 读 program_aliases 精确查表; 加 load_destinations。 - transform.py: 删 _identify_dest_univ/_strip_school/旧 _resolve_destination 启发式; identity 改用 canonical; 加 EXCLUDED_USER_IDS 屏蔽重复空 Rosie 草稿。 - _dump_raw.py: 只读脚本, 整齐打印每人原始数据供人工编纂(不做匹配)。 回归: xlsx 97 个 C 值 100% 逐字落地; 0 重复 abbrv 节点(碎片消除); CRN/Wheat 去向 作独立 Chosen 不绑被拒项目; Charlie/akk 等去向正确; mkdocs --strict 通过。 Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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…drop fuzzy matching
升学站「相同院校专业合并」与「最终去向(Q9)绑定」此前依赖 signature_tokens 特征词
改为人工逐人编纂的确定性权威表, 代码只做精确查表, 删除全部模糊逻辑:
回归: xlsx 97 个 C 值 100% 逐字落地; 0 重复 abbrv 节点(碎片消除); CRN/Wheat 去向 作独立 Chosen 不绑被拒项目; Charlie/akk 等去向正确; mkdocs --strict 通过。