Knowledge Tree
Relations (1)
related 2.32 — strongly supporting 4 facts
Knowledge extraction is a fundamental component of the knowledge graph construction pipeline, as evidenced by its inclusion in both traditional three-layered pipelines [1] and the broader quality assurance process [2]. Furthermore, knowledge extraction is recognized as a specific task within the unified generative frameworks [3] and existing benchmarks [4] used to evaluate knowledge graph construction.
Facts (4)
Sources
LLM-empowered knowledge graph construction: A survey - arXiv arxiv.org 2 facts
claimLarge Language Models are transforming Knowledge Graph construction by shifting the paradigm from rule-based and modular pipelines toward unified, adaptive, and generative frameworks across ontology engineering, knowledge extraction, and knowledge fusion.
claimTraditional Knowledge Graph construction follows a three-layered pipeline comprising ontology engineering, knowledge extraction, and knowledge fusion.
Construction of Knowledge Graphs: State and Challenges - arXiv arxiv.org 2 facts
claimQuality assurance is necessary throughout the entire Knowledge Graph construction process, including source selection, data cleaning, knowledge extraction, ontology evolution, and entity fusion.
claimExisting benchmarks for knowledge graph construction are currently limited to individual tasks such as knowledge extraction, ontology matching, entity resolution, and knowledge graph completion.