Research Article

A PROPOSED MODEL FOR ONTOLOGY BASED DEVELOPMENT OF SANSKRIT NAMED ENTITY RECOGNITION

by  Vini Gujarati, Veena Jokhakar
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Issue 62
Published: December 2025
Authors: Vini Gujarati, Veena Jokhakar
10.5120/ijca2025926025
PDF

Vini Gujarati, Veena Jokhakar . A PROPOSED MODEL FOR ONTOLOGY BASED DEVELOPMENT OF SANSKRIT NAMED ENTITY RECOGNITION. International Journal of Computer Applications. 187, 62 (December 2025), 46-49. DOI=10.5120/ijca2025926025

                        @article{ 10.5120/ijca2025926025,
                        author  = { Vini Gujarati,Veena Jokhakar },
                        title   = { A PROPOSED MODEL FOR ONTOLOGY BASED DEVELOPMENT OF SANSKRIT NAMED ENTITY RECOGNITION },
                        journal = { International Journal of Computer Applications },
                        year    = { 2025 },
                        volume  = { 187 },
                        number  = { 62 },
                        pages   = { 46-49 },
                        doi     = { 10.5120/ijca2025926025 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2025
                        %A Vini Gujarati
                        %A Veena Jokhakar
                        %T A PROPOSED MODEL FOR ONTOLOGY BASED DEVELOPMENT OF SANSKRIT NAMED ENTITY RECOGNITION%T 
                        %J International Journal of Computer Applications
                        %V 187
                        %N 62
                        %P 46-49
                        %R 10.5120/ijca2025926025
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

Named Entity Recognition (NER) is the task of identifying the entities in the text document and categorize them into pre-defined categories such as Person, Location, Organization, etc. It is an important step in the processing of natural text. This paper propose an NER system for Sanskrit language using ontology. In contrast to modern languages, the Sanskrit language has rich morphology, complex compounds and vast use of epithets (descriptive titles, alternative names) which makes entity identification more difficult. To address this problem, we proposed a Model that combines linguistic preprocessing and ontology-aware entity linking to ensure robust recognition of relationship between NEs in Sanskrit text.

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Index Terms
Computer Science
Information Sciences
Information Extraction
Natural Language Processing
Artificial Intelligence
Named Entity Recognition
Ontology
Keywords

Entity Identification Entity Chunking Machine Translation Information Retrieval Knowledge Graph Text Summarization

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