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ToNER: Type-oriented Named Entity Recognition with Generative Language Model
April 16, 2024, 4:51 a.m. | Guochao Jiang, Ziqin Luo, Yuchen Shi, Dixuan Wang, Jiaqing Liang, Deqing Yang
cs.CL updates on arXiv.org arxiv.org
Abstract: In recent years, the fine-tuned generative models have been proven more powerful than the previous tagging-based or span-based models on named entity recognition (NER) task. It has also been found that the information related to entities, such as entity types, can prompt a model to achieve NER better. However, it is not easy to determine the entity types indeed existing in the given sentence in advance, and inputting too many potential entity types would distract …
abstract arxiv cs.ai cs.cl found generative generative models information language language model ner prompt recognition tagging the information toner type types
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