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Multi-feature Chinese named entity recognition
四川大学学报. 自然科学版, 2022 The task of named entity recognition is to locate the entities in the text and classify them into predefined categories. The current mainstream Chinese named entity recognition models are characterbased named entity recognition models which word ...
XU Xiao-Bo +4 more
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Research Progress of Named Entity Recognition Based on Large Language Model [PDF]
Jisuanji kexue yu tansuoNamed entity recognition aims to identify named entities and their types from unstructured text, which is an important basic task in natural language processing technologies such as question answering system, machine translation and knowledge graph. With
LIANG Jia, ZHANG Liping, YAN Sheng, ZHAO Yubo, ZHANG Yawen
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Named Entity Recognition - Is There a Glass Ceiling? [PDF]
Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL), 2019 Accepted to CoNLL ...
Tomasz Stanislawek +4 more
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DroNER: Dataset for drone named entity recognition
Data in Brief, 2023 The dataset is constructed from the drone flight log messages extracted from publicly available drone image datasets provided by VTO Labs under the Drone Forensic Program.
Swardiantara Silalahi +2 more
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Biomedical Flat and Nested Named Entity Recognition: Methods, Challenges, and Advances
Applied SciencesBiomedical named entity recognition (BioNER) aims to identify and classify biomedical entities (i.e., diseases, chemicals, and genes) from text into predefined classes. This process serves as an important initial step in extracting biomedical information
Yesol Park, Gyujin Son, Mina Rho
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OWNER — Toward Unsupervised Open-World Named Entity Recognition
IEEE AccessNamed Entity Recognition (NER) is a crucial task in Natural Language Processing (NLP), traditionally addressed through supervised learning, which requires extensive annotated corpora. This requirement poses challenges, particularly in specialized domains
Pierre-Yves Genest +3 more
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Neural Architectures for Named Entity Recognition [PDF]
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2016 State-of-the-art named entity recognition systems rely heavily on hand-crafted features and domain-specific knowledge in order to learn effectively from the small, supervised training corpora that are available. In this paper, we introduce two new neural architectures---one based on bidirectional LSTMs and conditional random fields, and the other that ...
Lample, Guillaume +4 more
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Biomedical Named Entity Recognition at Scale [PDF]
, 2021 Named entity recognition (NER) is a widely applicable natural language processing task and building block of question answering, topic modeling, information retrieval, etc. In the medical domain, NER plays a crucial role by extracting meaningful chunks from clinical notes and reports, which are then fed to downstream tasks like assertion status ...
Veysel Kocaman, David Talby
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Neural Named Entity Recognition for Kazakh
, 2023 We present several neural networks to address the task of named entity recognition for morphologically complex languages (MCL). Kazakh is a morphologically complex language in which each root/stem can produce hundreds or thousands of variant word forms.
Gulmira Tolegen +3 more
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Code and Named Entity Recognition in StackOverflow [PDF]
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020 updated with better results. (To appear in ACL 2020)
Jeniya Tabassum +3 more
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