Results 41 to 50 of about 2,702,605 (333)

ANEC: An Amharic Named Entity Corpus and Transformer Based Recognizer

IEEE Access, 2023
Named Entity Recognition is an information extraction task that serves as a pre-processing step for other natural language processing tasks, such as machine translation, information retrieval, and question answering.
Ebrahim Chekol Jibril, A. Cuneyd Tantug
doaj   +1 more source

Comprehensive Overview of Named Entity Recognition: Models, Domain-Specific Applications and Challenges [PDF]

arXiv.org, 2023
In the domain of Natural Language Processing (NLP), Named Entity Recognition (NER) stands out as a pivotal mechanism for extracting structured insights from unstructured text.
Kalyani Pakhale
semanticscholar   +1 more source

Nested named entity recognition [PDF]

Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing Volume 1 - EMNLP '09, 2009
Many named entities contain other named entities inside them. Despite this fact, the field of named entity recognition has almost entirely ignored nested named entity recognition, but due to technological, rather than ideological reasons. In this paper, we present a new technique for recognizing nested named entities, by using a discriminative ...
Jenny Rose Finkel, Christopher D. Manning   +1 more
openaire   +2 more sources

Federated Named Entity Recognition

CoRR, 2022
We present an analysis of the performance of Federated Learning in a paradigmatic natural-language processing task: Named-Entity Recognition (NER). For our evaluation, we use the language-independent CoNLL-2003 dataset as our benchmark dataset and a Bi-LSTM-CRF model as our benchmark NER model.
Joel Mathew, Dimitris Stripelis, José Luis Ambite   +2 more
openaire   +3 more sources

PromptNER: Prompt Locating and Typing for Named Entity Recognition [PDF]

Annual Meeting of the Association for Computational Linguistics, 2023
Prompt learning is a new paradigm for utilizing pre-trained language models and has achieved great success in many tasks. To adopt prompt learning in the NER task, two kinds of methods have been explored from a pair of symmetric perspectives, populating ...
Yongliang Shen, Zeqi Tan, Shuhui Wu, Wenqi Zhang, Rongsheng Zhang, Yadong Xi, Weiming Lu, Y. Zhuang   +7 more
semanticscholar   +1 more source

Named Entity Extraction for Knowledge Graphs: A Literature Overview

IEEE Access, 2020
An enormous amount of digital information is expressed as natural-language (NL) text that is not easily processable by computers. Knowledge Graphs (KG) offer a widely used format for representing information in computer-processable form. Natural Language
Tareq Al-Moslmi, Marc Gallofre Ocana, Andreas L. Opdahl, Csaba Veres   +3 more
doaj   +1 more source

Named entity recognition method based on joint entity boundary detection

Journal of Hebei University of Science and Technology, 2023
To solve the problem that traditional named entity recognition methods cannot effectively utilize entity boundary information, a named entity recognition method based on joint entity boundary detection was proposed.
Xiaoteng LI, Zhinan GOU, Kai GAO
doaj   +1 more source

A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends [PDF]

IEEE Transactions on Knowledge and Data Engineering, 2023
As more and more Arabic texts emerged on the Internet, extracting important information from these Arabic texts is especially useful. As a fundamental technology, Named entity recognition (NER) serves as the core component in information extraction ...
Xiaoye Qu, Yingjie Gu, Qingrong Xia, Zechang Li, Zhefeng Wang, Baoxing Huai   +5 more
semanticscholar   +1 more source

Concept recognition as a machine translation problem

BMC Bioinformatics, 2021
Background Automated assignment of specific ontology concepts to mentions in text is a critical task in biomedical natural language processing, and the subject of many open shared tasks.
Mayla R. Boguslav, Negacy D. Hailu, Michael Bada, William A. Baumgartner, Lawrence E. Hunter   +4 more
doaj   +1 more source

MasakhaNER: Named Entity Recognition for African Languages

Transactions of the Association for Computational Linguistics, 2021
We take a step towards addressing the under- representation of the African continent in NLP research by bringing together different stakeholders to create the first large, publicly available, high-quality dataset for named entity recognition (NER) in ten
David Ifeoluwa Adelani, Jade Abbott, Graham Neubig, Daniel D’souza, Julia Kreutzer, Constantine Lignos, Chester Palen-Michel, Happy Buzaaba, Shruti Rijhwani, Sebastian Ruder, Stephen Mayhew, Israel Abebe Azime, Shamsuddeen H. Muhammad, Chris Chinenye Emezue, Joyce Nakatumba-Nabende, Perez Ogayo, Aremu Anuoluwapo, Catherine Gitau, Derguene Mbaye, Jesujoba Alabi, Seid Muhie Yimam, Tajuddeen Rabiu Gwadabe, Ignatius Ezeani, Rubungo Andre Niyongabo, Jonathan Mukiibi, Verrah Otiende, Iroro Orife, Davis David, Samba Ngom, Tosin Adewumi, Paul Rayson, Mofetoluwa Adeyemi, Gerald Muriuki, Emmanuel Anebi, Chiamaka Chukwuneke, Nkiruka Odu, Eric Peter Wairagala, Samuel Oyerinde, Clemencia Siro, Tobius Saul Bateesa, Temilola Oloyede, Yvonne Wambui, Victor Akinode, Deborah Nabagereka, Maurice Katusiime, Ayodele Awokoya, Mouhamadane MBOUP, Dibora Gebreyohannes, Henok Tilaye, Kelechi Nwaike, Degaga Wolde, Abdoulaye Faye, Blessing Sibanda, Orevaoghene Ahia, Bonaventure F. P. Dossou, Kelechi Ogueji, Thierno Ibrahima DIOP, Abdoulaye Diallo, Adewale Akinfaderin, Tendai Marengereke, Salomey Osei   +60 more
doaj   +1 more source