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基于医药知识图谱的智能问答系统
Insightful Tutorials and Papers about Knowledge Graphs
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)。
🤖 Neural SPARQL Machines for Knowledge Graph Question Answering.
You can find the most recent KGQA benchmark numbers from publications here.
Official code of the ACL 2025 paper "SimGRAG: Leveraging Similar Subgraphs for Knowledge Graphs Driven Retrieval-Augmented Generation"
[EMNLP Findings 2022] ReaRev: Adaptive Reasoning for Question Answering over Knowledge Graphs
[AAAI 2022] TempoQR: Temporal Question Reasoning over Knowledge Graphs
Code for our CIKM'21 paper "Complex Temporal Qestion Answering on Knowledge Graphs"
Explainable complex question answering over RDF files via Llama Index.
[WWW 2025] Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoning
Dataset Resplitting for Generalization in KGQA. See also https://github.com/semantic-systems/KGQA-datasets
Code and notebooks and data for the paper "Domain Specific Question Answering Over Knowledge Graphs Using Logical Programming and Large Language Models"
基于知识图谱的问答系统