title: OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction
    System
summary: We introduce OneKE, a dockerized schema-guided knowledge extraction system,
  which can extract knowledge from the Web and raw PDF Books, and support various
  domains (science, news, etc.). Specifically, we design OneKE with multiple
  agents and a configure knowledge base. Different agents perform their
  respective roles, enabling support for various extraction scenarios. The
  configure knowledge base facilitates schema configuration, error case debugging
  and correction, further improving the performance. Empirical evaluations on
  benchmark datasets demonstrate OneKE's efficacy, while case studies further
  elucidate its adaptability to diverse tasks across multiple domains,
  highlighting its potential for broad applications. We have open-sourced the
  Code at https://github.com/zjunlp/OneKE and released a Video at
  http://oneke.openkg.cn/demo.mp4.
paper_authors._id: 677368fbe182b937d5860758
paper_authors.name: Yujie Luo
paper_authors._id: 677368fbe182b937d5860759
paper_authors.name: Xiangyuan Ru
paper_authors._id: 677368fbe182b937d586075a
paper_authors.name: Kangwei Liu
paper_authors._id: 677368fbe182b937d586075b
paper_authors.name: Lin Yuan
paper_authors._id: 677368fbe182b937d586075c
paper_authors.name: Mengshu Sun
paper_authors._id: 677368fbe182b937d586075d
paper_authors.name: Ningyu Zhang
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-01-01T20:12:46.387Z
paper_authors._id: 620b3bbb0668e435407c8d0a
paper_authors.avatarUrl: /avatars/e0fccbb2577d76088e09f054c35cffbc.svg
paper_authors.fullname: Ningyu Zhang
paper_authors.type: user
paper_authors.user: Ningyu
paper_authors._id: 677368fbe182b937d586075e
paper_authors.name: Lei Liang
paper_authors._id: 677368fbe182b937d586075f
paper_authors.name: Zhiqiang Zhang
paper_authors._id: 677368fbe182b937d5860760
paper_authors.name: Jun Zhou
paper_authors._id: 677368fbe182b937d5860761
paper_authors.name: Lanning Wei
paper_authors._id: 677368fbe182b937d5860762
paper_authors.name: Da Zheng
paper_authors._id: 677368fbe182b937d5860763
paper_authors.name: Haofen Wang
paper_authors._id: 677368fbe182b937d5860764
paper_authors.name: Huajun Chen
paper_title: OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction
    System
paper_summary: We introduce OneKE, a dockerized schema-guided knowledge extraction system,
  which can extract knowledge from the Web and raw PDF Books, and support various
  domains (science, news, etc.). Specifically, we design OneKE with multiple
  agents and a configure knowledge base. Different agents perform their
  respective roles, enabling support for various extraction scenarios. The
  configure knowledge base facilitates schema configuration, error case debugging
  and correction, further improving the performance. Empirical evaluations on
  benchmark datasets demonstrate OneKE's efficacy, while case studies further
  elucidate its adaptability to diverse tasks across multiple domains,
  highlighting its potential for broad applications. We have open-sourced the
  Code at https://github.com/zjunlp/OneKE and released a Video at
  http://oneke.openkg.cn/demo.mp4.