An Approach to Ontology-Driven Pro-cessing of Scientific Texts and Us-er Natural Language Queries

Authors

  • Oleksandr Palagin
  • Mykola Petrenko
  • Dmytro Vykhovanets
  • Mykola Boyko

Keywords:

ontology engineering, semantic web technologies, scientific texts, knowledge graph, OWL ontology, RDF triples, logical inference

Abstract

This research presents a method and system architecture for ontology-driven processing of scientific natural-language texts that integrates a linguistic processor, a domain OWL ontology, a reasoning engine, and a knowledge graph. The system constructs a consistent knowledge graph suitable for the automatic interpretation of structurally complex user queries with subsequent transformation into SPARQL queries. The proposed pipeline includes formal mappings of linguistic analysis results to ontology classes, properties, and assertions; consistency checking; fact materialization; and an explanation mechanism that derives minimal sets of axioms and facts to justify the reasoning engine’s conclusions or to identify the causes of inconsistency. The output is a set of consistency-compliant subject–predicate–object triples. An ontology-consistency evaluation metric is introduced as the proportion of triples in the knowledge graph that do not violate ontological constraints, and the impact of logical processing on the harmonic mean of precision and recall for triple extraction is evaluated on a representative corpus of scientific texts in the field of knowledge engineering.

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Published

2026-03-31

How to Cite

Palagin, O., Petrenko, M., Vykhovanets, D., & Boyko, M. (2026). An Approach to Ontology-Driven Pro-cessing of Scientific Texts and Us-er Natural Language Queries. International Journal of Computing, 25(1), 39-47. Retrieved from https://www.computingonline.net/computing/article/view/4486

Issue

2026, Volume 25, Issue 1

Section

Articles

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