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SEMANTIC ROLE LABELING (SRL) FOR THE DISAMBIGUATION OF NATURAL LANGUAGE PROCESSING (NLP) SYSTEMS IN LOW-RESOURCED LANGUAGES AS KYRGYZ LANGUAGE

Cognitive analyses of the language by humans cover all components of the language, currently this requires from the machine as well. And widely used languages such as English NLP machines almost reach the level of performing this analysis coherently as humans do. Which started in accordance with Cho...

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Main Authors: Zhumakadyrova, N. Sh, Norazuna, Norahim, Mohamad Hardyman, Barawi
Format: Article
Language:English
Published: Issyk-Kul State University 2024
Subjects:
P Philology. Linguistics
Online Access:http://ir.unimas.my/id/eprint/47273/1/SEMANTIC%20ROLE%20LABELING%20%28SRL%29%20FOR%20THE.pdf
http://ir.unimas.my/id/eprint/47273/
https://www.elibrary.ru/item.asp?id=75095075
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spelling my.unimas.ir-472732025-01-06T01:22:38Z http://ir.unimas.my/id/eprint/47273/ SEMANTIC ROLE LABELING (SRL) FOR THE DISAMBIGUATION OF NATURAL LANGUAGE PROCESSING (NLP) SYSTEMS IN LOW-RESOURCED LANGUAGES AS KYRGYZ LANGUAGE Zhumakadyrova, N. Sh Norazuna, Norahim Mohamad Hardyman, Barawi P Philology. Linguistics Cognitive analyses of the language by humans cover all components of the language, currently this requires from the machine as well. And widely used languages such as English NLP machines almost reach the level of performing this analysis coherently as humans do. Which started in accordance with Chomsky's Universal grammar theory to analyze language via algorithms which were implemented according to the language syntactical structure. However, experience has shown that there is a linguistic features which algorithm based just on language structure can’t analyze accurately as humans does. One of the reasons for this is that every word can have various grammatical and semantic features according to its particular context. Specifically in the case of languages with flexible word order. So NLP machines in such morphologically rich agglutinative languages such as Kyrgyz, need to cover both nature (grammatical, semantical) of the word to enhance the accuracy level of the tool. Thus this work will analyze the word’s semantic meaning beside grammatical features such as word correlation (who did what to whom, when and where). Thus this paper will investigate the challenges of implementing Semantic Role Labeling (SRL) in the context of the Kyrgyz language, a low-resourced language, by examining its unique linguistic properties and the limitations of existing NLP tools. With identification and analysis of the specific challenges faced by the SRL model in handling ambiguous or complex sentences in the Kyrgyz language, providing insights into areas for future improvements. Issyk-Kul State University 2024 Article PeerReviewed text en http://ir.unimas.my/id/eprint/47273/1/SEMANTIC%20ROLE%20LABELING%20%28SRL%29%20FOR%20THE.pdf Zhumakadyrova, N. Sh and Norazuna, Norahim and Mohamad Hardyman, Barawi (2024) SEMANTIC ROLE LABELING (SRL) FOR THE DISAMBIGUATION OF NATURAL LANGUAGE PROCESSING (NLP) SYSTEMS IN LOW-RESOURCED LANGUAGES AS KYRGYZ LANGUAGE. BULLETIN OF ISSYK-KUL UNIVERSITY, 59. pp. 278-284. ISSN 1694-8211 https://www.elibrary.ru/item.asp?id=75095075 DOI: 10.69722/1694-8211-2024-59-278-284
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic P Philology. Linguistics
spellingShingle P Philology. Linguistics
Zhumakadyrova, N. Sh
Norazuna, Norahim
Mohamad Hardyman, Barawi
SEMANTIC ROLE LABELING (SRL) FOR THE DISAMBIGUATION OF NATURAL LANGUAGE PROCESSING (NLP) SYSTEMS IN LOW-RESOURCED LANGUAGES AS KYRGYZ LANGUAGE
description Cognitive analyses of the language by humans cover all components of the language, currently this requires from the machine as well. And widely used languages such as English NLP machines almost reach the level of performing this analysis coherently as humans do. Which started in accordance with Chomsky's Universal grammar theory to analyze language via algorithms which were implemented according to the language syntactical structure. However, experience has shown that there is a linguistic features which algorithm based just on language structure can’t analyze accurately as humans does. One of the reasons for this is that every word can have various grammatical and semantic features according to its particular context. Specifically in the case of languages with flexible word order. So NLP machines in such morphologically rich agglutinative languages such as Kyrgyz, need to cover both nature (grammatical, semantical) of the word to enhance the accuracy level of the tool. Thus this work will analyze the word’s semantic meaning beside grammatical features such as word correlation (who did what to whom, when and where). Thus this paper will investigate the challenges of implementing Semantic Role Labeling (SRL) in the context of the Kyrgyz language, a low-resourced language, by examining its unique linguistic properties and the limitations of existing NLP tools. With identification and analysis of the specific challenges faced by the SRL model in handling ambiguous or complex sentences in the Kyrgyz language, providing insights into areas for future improvements.
format Article
author Zhumakadyrova, N. Sh
Norazuna, Norahim
Mohamad Hardyman, Barawi
author_facet Zhumakadyrova, N. Sh
Norazuna, Norahim
Mohamad Hardyman, Barawi
author_sort Zhumakadyrova, N. Sh
title SEMANTIC ROLE LABELING (SRL) FOR THE DISAMBIGUATION OF NATURAL LANGUAGE PROCESSING (NLP) SYSTEMS IN LOW-RESOURCED LANGUAGES AS KYRGYZ LANGUAGE
title_short SEMANTIC ROLE LABELING (SRL) FOR THE DISAMBIGUATION OF NATURAL LANGUAGE PROCESSING (NLP) SYSTEMS IN LOW-RESOURCED LANGUAGES AS KYRGYZ LANGUAGE
title_full SEMANTIC ROLE LABELING (SRL) FOR THE DISAMBIGUATION OF NATURAL LANGUAGE PROCESSING (NLP) SYSTEMS IN LOW-RESOURCED LANGUAGES AS KYRGYZ LANGUAGE
title_fullStr SEMANTIC ROLE LABELING (SRL) FOR THE DISAMBIGUATION OF NATURAL LANGUAGE PROCESSING (NLP) SYSTEMS IN LOW-RESOURCED LANGUAGES AS KYRGYZ LANGUAGE
title_full_unstemmed SEMANTIC ROLE LABELING (SRL) FOR THE DISAMBIGUATION OF NATURAL LANGUAGE PROCESSING (NLP) SYSTEMS IN LOW-RESOURCED LANGUAGES AS KYRGYZ LANGUAGE
title_sort semantic role labeling (srl) for the disambiguation of natural language processing (nlp) systems in low-resourced languages as kyrgyz language
publisher Issyk-Kul State University
publishDate 2024
url http://ir.unimas.my/id/eprint/47273/1/SEMANTIC%20ROLE%20LABELING%20%28SRL%29%20FOR%20THE.pdf
http://ir.unimas.my/id/eprint/47273/
https://www.elibrary.ru/item.asp?id=75095075
_version_ 1821007930510540800
score 13.23648

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