Named Entity Recognition for Urdu Language: The UNER System, A Hybrid Approach
NER is a natural language processing technique that primarily classifies parts of parsed text into well-known named entities. In the domain of natural language processing, the recognition of name entities is used to classify nouns that appear in bulk text data and place these nouns into predefined g...
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| Format: | Article |
| Language: | English |
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University of Sindh
2022-09-01
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| Series: | University of Sindh Journal of Information and Communication Technology |
| Subjects: | |
| Online Access: | https://sujo.usindh.edu.pk/index.php/USJICT/article/view/6281 |
| _version_ | 1797805709389201408 |
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| author | Saba Rani Hira Fatima Naqvi Fida Hussain Khoso Attia Agha Dil Nawaz Hakro |
| author_facet | Saba Rani Hira Fatima Naqvi Fida Hussain Khoso Attia Agha Dil Nawaz Hakro |
| author_sort | Saba Rani |
| collection | DOAJ |
| description | NER is a natural language processing technique that primarily classifies parts of parsed text into well-known named entities. In the domain of natural language processing, the recognition of name entities is used to classify nouns that appear in bulk text data and place these nouns into predefined groups, such as names of people, places, times, dates, organizations, etc. There is a lot of fragmented material and data on the Cyberspace, therefore scholars are working on several languages (i.e: Sindhi, English, etc.), by working on various approaches and techniques depending on their locations, to improve accessibility of filtered information for online users. The NER enhance the quality of NLP in applications including automated summarization, semantic web search, information extraction and retrieval machine translation and question answering, chatbots and others. This study designs an efficient framework to extract noun entities in Urdu using a hybrid approach. The UNER system not only extracts entities by searching through a list of names, but also extracts named entities by recognizing phrases in a given text. The UNER system is designed to recognize Urdu noun entities in pre-defined categories such as places, personal names, titled personal names, organizations, object names, trade names, abbreviations, dates and times, measurements, and text names in Urdu. |
| first_indexed | 2024-03-13T05:55:04Z |
| format | Article |
| id | doaj.art-a4470a6be41d4d1ea0260b2d1d660952 |
| institution | Directory Open Access Journal |
| issn | 2521-5582 2523-1235 |
| language | English |
| last_indexed | 2024-03-13T05:55:04Z |
| publishDate | 2022-09-01 |
| publisher | University of Sindh |
| record_format | Article |
| series | University of Sindh Journal of Information and Communication Technology |
| spelling | doaj.art-a4470a6be41d4d1ea0260b2d1d6609522023-06-13T06:04:24ZengUniversity of SindhUniversity of Sindh Journal of Information and Communication Technology2521-55822523-12352022-09-01631081146281Named Entity Recognition for Urdu Language: The UNER System, A Hybrid ApproachSaba Rani0Hira Fatima Naqvi1Fida Hussain Khoso2Attia Agha3Dil Nawaz Hakro4Faculty of Engineering and Technology, University of Sindh, JamshoroInstitute of Mathematics and Computer Sciences, University of Sindh, JamshoroDawood University of Engineering and Technology, KarachiDawood University of Engineering and Technology, KarachiFaculty of Engineering and Technology, University of Sindh, JamshoroNER is a natural language processing technique that primarily classifies parts of parsed text into well-known named entities. In the domain of natural language processing, the recognition of name entities is used to classify nouns that appear in bulk text data and place these nouns into predefined groups, such as names of people, places, times, dates, organizations, etc. There is a lot of fragmented material and data on the Cyberspace, therefore scholars are working on several languages (i.e: Sindhi, English, etc.), by working on various approaches and techniques depending on their locations, to improve accessibility of filtered information for online users. The NER enhance the quality of NLP in applications including automated summarization, semantic web search, information extraction and retrieval machine translation and question answering, chatbots and others. This study designs an efficient framework to extract noun entities in Urdu using a hybrid approach. The UNER system not only extracts entities by searching through a list of names, but also extracts named entities by recognizing phrases in a given text. The UNER system is designed to recognize Urdu noun entities in pre-defined categories such as places, personal names, titled personal names, organizations, object names, trade names, abbreviations, dates and times, measurements, and text names in Urdu.https://sujo.usindh.edu.pk/index.php/USJICT/article/view/6281unernlp nerurdu, recognitionnamed entity |
| spellingShingle | Saba Rani Hira Fatima Naqvi Fida Hussain Khoso Attia Agha Dil Nawaz Hakro Named Entity Recognition for Urdu Language: The UNER System, A Hybrid Approach University of Sindh Journal of Information and Communication Technology uner nlp ner urdu, recognition named entity |
| title | Named Entity Recognition for Urdu Language: The UNER System, A Hybrid Approach |
| title_full | Named Entity Recognition for Urdu Language: The UNER System, A Hybrid Approach |
| title_fullStr | Named Entity Recognition for Urdu Language: The UNER System, A Hybrid Approach |
| title_full_unstemmed | Named Entity Recognition for Urdu Language: The UNER System, A Hybrid Approach |
| title_short | Named Entity Recognition for Urdu Language: The UNER System, A Hybrid Approach |
| title_sort | named entity recognition for urdu language the uner system a hybrid approach |
| topic | uner nlp ner urdu, recognition named entity |
| url | https://sujo.usindh.edu.pk/index.php/USJICT/article/view/6281 |
| work_keys_str_mv | AT sabarani namedentityrecognitionforurdulanguagetheunersystemahybridapproach AT hirafatimanaqvi namedentityrecognitionforurdulanguagetheunersystemahybridapproach AT fidahussainkhoso namedentityrecognitionforurdulanguagetheunersystemahybridapproach AT attiaagha namedentityrecognitionforurdulanguagetheunersystemahybridapproach AT dilnawazhakro namedentityrecognitionforurdulanguagetheunersystemahybridapproach |