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f8c91e8854
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>
31 lines
892 B
Markdown
31 lines
892 B
Markdown
请从以下带行号索引的简历文本中提取教育背景。
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{indexed_text}
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提取为 JSON:
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{{
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"education": [
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{{
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"school": "",
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"major": "",
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"degree": "",
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"department": "",
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"start_date": "",
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"end_date": "",
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"desc_lines": [start_index, end_index]
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}}
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]
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}}
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字段说明:
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- school: 学校全称，如"厦门大学"，中英文都可以
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- major: 专业，如"机械工程"
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- degree: 学位，本科/硕士/博士/专科/高中/初中，若不存在则填""
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- department: 系/学院，如"信息工程系"
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- start_date: 开始时间，格式为 %Y.%m 或 %Y
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- end_date: 结束时间，若至今填写"至今"，若不存在填写""
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- desc_lines: [起始行号, 结束行号]，教育描述对应的行号范围（可选）
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- 包括课程成绩、研究方向、GPA、荣誉奖项等
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- 不存在则填 []
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只返回 JSON。 /no_think |