 |
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
|
Issue: March 2026
Volume 11 | Issue 3
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21574
Article Published : 8528
Total Authors : 22430
Total Reviewer : 805
Total Countries : 159
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | Ontology-Guided Closed-Loop Reasoning Framework for Domain-Consistent Logic Validation in Large Language Models |
| Authors Name: | Saraswathi Sivamani , Ji Hwan Park |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_207740
|
| Published Paper Id: | IJRTI2511105 |
| Published In: | Volume 10 Issue 11, November-2025 |
| DOI: | |
| Abstract: | Abstract: Large language models (LLMs) can generate fluent causal statements, but their outputs often lack domain fidelity, leading to hallucinated, inconsistent, or scientifically invalid relations. This work presents an ontology-guided semantic validation framework that evaluates whether LLM-generated cause–effect statements conform to domain-approved causal rules. The framework integrates an ontology-based similarity validator, a hybrid retrieval mechanism for selecting the most relevant domain rule, and a lightweight domain-projection component (T_domain) that enhances semantic grounding during validation. A controlled dataset of one hundred causal statements was constructed across three operational domains—energy, water, and agriculture—to evaluate the system under three configurations: (1) No Ontology, (2) Ontology Only, and (3) Ontology + T_domain. Results using Sentence-T5-large embeddings show that ontology grounding substantially improves separation between valid and invalid causal relations, while domain projection further reduces borderline classification errors and stabilizes similarity scores across diverse linguistic patterns. Visual analyses, including distribution plots and sample-level comparisons, confirm that the proposed approach yields more reliable and domain-consistent causal validations than unconstrained LLM reasoning. The findings highlight the effectiveness of combining symbolic domain knowledge with embedding-based semantic validation and demonstrate the potential of the framework as a lightweight verification layer for safety-critical or knowledge-regulated applications. |
| Keywords: | Ontology-Guided Reasoning, Causal Inference, Domain Validation, Semantic Similarity |
| Cite Article: | "Ontology-Guided Closed-Loop Reasoning Framework for Domain-Consistent Logic Validation in Large Language Models", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 11, page no.b30-b37, November-2025, Available :http://www.ijrti.org/papers/IJRTI2511105.pdf |
| Downloads: | 000215 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2511105
Registration ID:207740
Published In: Volume 10 Issue 11, November-2025
DOI (Digital Object Identifier):
Page No: b30-b37 Country: Seoul, Seoul, Korea Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2511105 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2511105 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2026 - All Rights Reserved - IJRTI | |||