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Core optimizations (refer to arXiv:2510.09722): 1. PDF text fusion: Metadata + OCR dual-path extraction and fusion 2. Page-aware reconstruction: YOLOv10 page segmentation + hierarchical sorting + line number indexing 3. Parallel task decomposition: Basic information/work experience/educational background three-way parallel LLM extraction 4. Index pointer mechanism: LLM returns a range of line numbers instead of generating the full text, reducing the illusion of full text. --------- Co-authored-by: Aron.Yao <yaowei@yaoweideMacBook-Pro.local> Co-authored-by: Aron.Yao <yaowei@192.168.1.68> Co-authored-by: Yingfeng <yingfeng.zhang@gmail.com>
39 lines
1.3 KiB
Markdown
39 lines
1.3 KiB
Markdown
请从以下带行号索引的简历文本中提取基本信息。
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{indexed_text}
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提取如下信息到 JSON，若某些字段不存在则输出 "" 空或 0:
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{{
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"name_kwd": "",
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"gender_kwd": "",
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"age_int": 0,
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"phone_kwd": "",
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"email_tks": "",
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"birth_dt": "",
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"work_exp_flt": 0,
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"current_location": "",
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"expect_city_names_tks": [],
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"expect_position_name_tks": [],
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"skill_tks": [],
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"language_tks": [],
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"certificate_tks": [],
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"self_evaluation_tks": ""
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}}
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字段说明:
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- name_kwd: 姓名，如"张三"
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- gender_kwd: 男/女，若不存在则不填
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- age_int: 当前年龄，整数
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- phone_kwd: 电话/手机，请保留原文中的形式，保留国家码区号括号
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- email_tks: 邮箱，如 "xxx@qq.com"
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- birth_dt: 出生年月，如 "1996-11"
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- work_exp_flt: 工作年限，浮点数
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- current_location: 现居地/当前城市，不要从工作经历中推测，要写明现居地
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- expect_city_names_tks: 期望工作城市列表，简历中需要明确说明是期望城市
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- expect_position_name_tks: 期望职位列表
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- skill_tks: 技能/技术栈列表
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- language_tks: 语言能力列表
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- certificate_tks: 证书/资质列表
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- self_evaluation_tks: 自我评价/个人优势/个人总结，完整提取原文内容
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只返回 JSON。 /no_think |