OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction
  System
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.
677368fbe182b937d5860758
Yujie Luo
677368fbe182b937d5860759
Xiangyuan Ru
677368fbe182b937d586075a
Kangwei Liu
677368fbe182b937d586075b
Lin Yuan
677368fbe182b937d586075c
Mengshu Sun
677368fbe182b937d586075d
Ningyu Zhang
claimed_verified
2025-01-01T20:12:46.387Z
620b3bbb0668e435407c8d0a
/avatars/e0fccbb2577d76088e09f054c35cffbc.svg
Ningyu Zhang
user
Ningyu
677368fbe182b937d586075e
Lei Liang
677368fbe182b937d586075f
Zhiqiang Zhang
677368fbe182b937d5860760
Jun Zhou
677368fbe182b937d5860761
Lanning Wei
677368fbe182b937d5860762
Da Zheng
677368fbe182b937d5860763
Haofen Wang
677368fbe182b937d5860764
Huajun Chen
OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction
  System
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.
OneKE is a dockerized schema-guided knowledge extraction system that extracts knowledge from the Web and PDFs using multiple agents and a configurable knowledge base, effective across various domains.
schema-guided knowledge extraction dockerized agents configurable knowledge base