Open Local Knowledge Graph Construction from Academic Papers Using Generative Large Language Models
This manuscript introduces paper2lkg, a novel Local Knowledge Graph Construction (KGC) pipeline designed to transform individual academic papers into their structured local Knowledge Graph (KG) representations.The pipeline harnesses Large Language Models (LLMs), particularly generative LLMs, to automate key Natural Language Processing (NLP) tasks in KGC.The constructed local KGs can potentially be used to enrich an existing academic KG that lacks detailed local representations of individual papers or further integrated into new academic KGs through Knowledge Graph Alignment (KGA).
Authors
- Pouya Ghiasnezhad Omran (ORCID: https://orcid.org/0000-0002-4473-3877)
- Haoting Chen (ORCID: https://orcid.org/0000-0001-9351-8690)
- Sergio José Rodríguez Méndez (ORCID: https://orcid.org/0000-0001-7203-8399)
Institutions
- Australian National University (AU)
Publication Details
- Published
- 2025-05-08
- DOI
- https://doi.org/10.1145/3701716.3717820
- Citations
- 1
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 2.48