Results 21 to 30 of about 379,251 (377)
DiffusionNER: Boundary Diffusion for Named Entity Recognition [PDF]
Annual Meeting of the Association for Computational Linguistics, 2023 In this paper, we propose DiffusionNER, which formulates the named entity recognition task as a boundary-denoising diffusion process and thus generates named entities from noisy spans.
Yongliang Shen +5 more
semanticscholar +1 more source
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 +7 more
semanticscholar +1 more source
Template-Based Named Entity Recognition Using BART [PDF]
Findings, 2021 There is a recent interest in investigating few-shot NER, where the low-resource target domain has different label sets compared with a resource-rich source domain. Existing methods use a similarity-based metric.
Leyang Cui +4 more
semanticscholar +1 more source
Named Entity Recognition for Spoken Finnish [PDF]
Proceedings of the 2nd International Workshop on AI for Smart TV Content Production, Access and Delivery, 2020 In this paper we present a Bidirectional LSTM neural network with a Conditional Random Field layer on top, which utilizes word, character and morph embeddings in order to perform named entity recognition on various Finnish datasets. To overcome the lack of annotated training corpora that arises when dealing with low-resource languages like Finnish, we ...
Leinonen, Juho +3 more
openaire +4 more sources
Review of Chinese Named Entity Recognition Research [PDF]
Jisuanji kexue yu tansuo, 2023 With the rapid development of related technologies in the field of natural language processing, as an upstream task of natural language processing, improving the accuracy of named entity recognition is of great significance for subsequent text processing
WANG Yingjie, ZHANG Chengye, BAI Fengbo, WANG Zumin, JI Changqing
doaj +1 more source
Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition [PDF]
Conference on Computational Natural Language Learning, 2003 We describe the CoNLL-2003 shared task: language-independent named entity recognition. We give background information on the data sets (English and German) and the evaluation method, present a general overview of the systems that have taken part in the ...
E. Tjong Kim Sang, F. D. Meulder
semanticscholar +1 more source
Unified Named Entity Recognition as Word-Word Relation Classification [PDF]
AAAI Conference on Artificial Intelligence, 2021 So far, named entity recognition (NER) has been involved with three major types, including flat, overlapped (aka. nested), and discontinuous NER, which have mostly been studied individually.
Jingye Li +7 more
semanticscholar +1 more source
Indirectly Named Entity Recognition
Journal of Computer-Assisted Linguistic Research, 2021 We define here indirectly named entities, as a term to denote multiword expressions referring to known named entities by means of periphrasis. While named entity recognition is a classical task in natural language processing, little attention has been paid to indirectly named entities and their treatment.
Kauffmann, Alexis +6 more
openaire +4 more sources
BERN2: an advanced neural biomedical named entity recognition and normalization tool [PDF]
Bioinform., 2022 In biomedical natural language processing, named entity recognition (NER) and named entity normalization (NEN) are key tasks that enable the automatic extraction of biomedical entities (e.g. diseases and drugs) from the ever-growing biomedical literature.
Mujeen Sung +5 more
semanticscholar +1 more source
A Chinese Named Entity Recognition Method Based on ERNIE-BiLSTM-CRF for Food Safety Domain
Applied Sciences, 2023 Food safety is closely related to human health. Therefore, named entity recognition technology is used to extract named entities related to food safety, and building a regulatory knowledge graph in the field of food safety can help relevant authorities ...
Qing Li, Weibing Wan, Yuming Zhao
semanticscholar +1 more source