arXiv:2001.04351
공식 코드 · Papers with Code
CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for Chinese
원문 초록
In this paper, we introduce the NER dataset from CLUE organization (CLUENER2020), a well-defined fine-grained dataset for named entity recognition in Chinese. CLUENER2020 contains 10 categories. Apart from common labels like person, organization, and location, it contains more diverse categories. It is more challenging than current other Chinese NER datasets and could better reflect real-world applications. For comparison, we implement several state-of-the-art baselines as sequence labeling tasks and report human performance, as well as its analysis. To facilitate future work on fine-grained NER for Chinese, we release our dataset, baselines, and leader-board.
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Student-Powered Digital Scholarship CoLab Project in the HKUST Library: Develop a Chinese Named-Entity Recognition (NER) Tool within One Semester from the Ground Up
Logits-Constrained Framework with RoBERTa for Ancient Chinese NER
CRENER: A Character Relation Enhanced Chinese NER Model
Selecting and Merging: Towards Adaptable and Scalable Named Entity Recognition with Large Language Models
Label-Guided In-Context Learning for Named Entity Recognition
Named Entity Recognition in Historical Italian: The Case of Giacomo Leopardi's Zibaldone
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