LLM-guided ontology construction from unstructured texts
A new approach combines compact open-source Large Language Models (LLMs) with ontology learning to extract and structure knowledge from industrial text. This paper evaluates the method on a private French corpus of power-grid incident reports, using LLMs ranging from 7B to 32B parameters. The process extracts entities and relations, generates RDF triples, constructs an OWL ontology, enriches it…
Key points
- Combines compact LLMs with ontology learning for text processing
- Evaluates approach on French power-grid incident reports corpus
- Improves extraction quality with schema-guided prompting and quantized models
The story so far
2 episodes →- LLM-guided ontology construction from unstructured textsthis story
The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.
More in Research
All →- LLM-generated ACSL contracts for numerical libraries · 1 src
- Visualizing RAG Conflicts: Temporal Semantic Divergence Score · 1 src
- Study suggests dialects do not drive jailbreak success · 1 src
- Researchers test 72,000 RAG combos on Indian government documents · 1 src
- Researchers release ChestPheNoT for auditable radiology report analysis · 1 src
Comments
via GitHub Discussions