Statistics for topic relation-extraction
RepositoryStats tracks 642,926 Github repositories, of these 115 are tagged with the relation-extraction topic. The most common primary language for repositories using this topic is Python (85).
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Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
[EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and Construction
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
[EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and Construction
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
[EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and Construction
Retrieve, Read and LinK: Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget (ACL 2024)
农业知识图谱(AgriKG):农业领域的信息检索,命名实体识别,关系抽取,智能问答,辅助决策
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
Retrieve, Read and LinK: Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget (ACL 2024)
Generalist and Lightweight Model for Relation Extraction (Extract any relationship types from text)
[EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and Construction
农业知识图谱(AgriKG):农业领域的信息检索,命名实体识别,关系抽取,智能问答,辅助决策
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
[WWW 2025] A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System.
医药知识图谱自动问答系统实现,包括构建知识图谱、基于知识图谱的流水线问答以及前端实现。实体识别(基于词典+BERT_CRF)、实体链接(Sentence-BERT做匹配)、意图识别(基于提问词+领域词词典)。
Generalist and Lightweight Model for Relation Extraction (Extract any relationship types from text)
Generalist and Lightweight Model for Relation Extraction (Extract any relationship types from text)
[WWW 2025] A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System.
[EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and Construction
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
Retrieve, Read and LinK: Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget (ACL 2024)
农业知识图谱(AgriKG):农业领域的信息检索,命名实体识别,关系抽取,智能问答,辅助决策
This is a meta-model distilled from LLMs for information extraction. This is an intermediate checkpoint that can be well-transferred to all kinds of downstream information extraction tasks.
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
Guideline following Large Language Model for Information Extraction