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Prompt-Based Word-Level Information Injection BERT for Chinese Named Entity Recognition
Applied Sciences, 2023 Named entity recognition (NER) is a subfield of natural language processing (NLP) that identifies and classifies entities from plain text, such as people, organizations, locations, and other types.
Qiang He +3 more
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Applied Sciences, 2023 Named entity recognition (NER) is a fundamental task in natural language processing. In Chinese NER, additional resources such as lexicons, syntactic features and knowledge graphs are usually introduced to improve the recognition performance of the model.
Ruiming Gu +3 more
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An ERNIE-Based Joint Model for Chinese Named Entity Recognition
Applied Sciences, 2020 Named Entity Recognition (NER) is the fundamental task for Natural Language Processing (NLP) and the initial step in building a Knowledge Graph (KG). Recently, BERT (Bidirectional Encoder Representations from Transformers), which is a pre-training model,
Yu Wang +4 more
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Mathematics, 2022 Extracting structured information from massive and heterogeneous text is a hot research topic in the field of natural language processing. It includes two key technologies: named entity recognition (NER) and relation extraction (RE).
Li-Xin Liang +4 more
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Chinese Named Entity Recognition Model Based on Transformer Encoder [PDF]
Jisuanji gongcheng, 2022 Named Entity Recognition(NER) is an important task in Natural Language Processing(NLP), and compared with English NER, Chinese NER is often more difficult to achieve.Traditional Chinese entity recognition models are usually based on deep neural networks ...
SI Yichen, GUAN Youqing
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FLAT: Chinese NER Using Flat-Lattice Transformer [PDF]
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020 Recently, the character-word lattice structure has been proved to be effective for Chinese named entity recognition (NER) by incorporating the word information. However, since the lattice structure is complex and dynamic, most existing lattice-based models are hard to fully utilize the parallel computation of GPUs and usually have a low inference-speed.
Xiaonan Li +3 more
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SLK-NER: Exploiting Second-order Lexicon Knowledge for Chinese NER
CoRR, 2020 5 pages, The work is accepted by ...
Dou Hu 0001, Lingwei Wei
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CNN-Based Chinese NER with Lexicon Rethinking [PDF]
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019 Character-level Chinese named entity recognition (NER) that applies long short-term memory (LSTM) to incorporate lexicons has achieved great success. However, this method fails to fully exploit GPU parallelism and candidate lexicons can conflict. In this work, we propose a faster alternative to Chinese NER: a convolutional neural network (CNN)-based ...
Tao Gui +5 more
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Study on Chinese Named Entity Extraction Rules Based on Boundary Location and Correction [PDF]
Jisuanji kexue, 2023 Compared with English text which is naturally composed of words,Chinese text has no word delimiters,so the combination of Chinese characters is more flexible,and it's more difficult to determine the entity boundaries in Chinese named entity recognition ...
LIU Pan, GUO Yanming, LEI Jun, LAO Mingrui, LI Guohui
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