mirror of
https://github.com/infiniflow/ragflow.git
synced 2026-07-27 10:52:03 +08:00
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>
892 B
892 B
请从以下带行号索引的简历文本中提取教育背景。
{indexed_text}
提取为 JSON: {{ "education": [ {{ "school": "", "major": "", "degree": "", "department": "", "start_date": "", "end_date": "", "desc_lines": [start_index, end_index] }} ] }}
字段说明:
- school: 学校全称,如"厦门大学",中英文都可以
- major: 专业,如"机械工程"
- degree: 学位,本科/硕士/博士/专科/高中/初中,若不存在则填""
- department: 系/学院,如"信息工程系"
- start_date: 开始时间,格式为 %Y.%m 或 %Y
- end_date: 结束时间,若至今填写"至今",若不存在填写""
- desc_lines: [起始行号, 结束行号],教育描述对应的行号范围(可选)
- 包括课程成绩、研究方向、GPA、荣誉奖项等
- 不存在则填 []
只返回 JSON。 /no_think