该数据集是一个用于命名实体识别（NER）任务的结构化数据集，包含三个主要字段：'text'（原始文本）、'tokens'（分词序列）和'ner_tags'（命名实体标签序列）。命名实体标签共分为8类，包括动作（Action）、概念（Concept）、谓词（Predicate）、引用（Reference）及其相应的起始（B-）和中间（I-）标签，以及普通标签（O）。数据集分为训练集（800个样本）、

Hugging Face2026-02-07 更新90

X-qi/msra_ner

实体识别

自然语言处理

--- annotations_creators: - crowdsourced language_creators: - found language: - zh license: - unknown multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_cate

Hugging Face2026-03-21 更新80

nlpso/m1_fine_tuning_ref_cmbert_iob2

实体识别

自然语言处理

--- language: - fr multilinguality: - monolingual task_categories: - token-classification --- # m1_fine_tuning_ref_cmbert_iob2 ## Introduction This dataset was used to fine-tuned [Jean-Baptiste/cam

Hugging Face2023-02-22 更新100

ISSAI KazNERD

实体识别

哈萨克语

Kazakh named entity recognition dataset (KazNERD) contains 112,702 sentences from the television news domain and 136,333 annotations for 25 entity classes. All named entities were labelled using the I

DataCite Commons2021-11-27 更新90

maybe1991/chinese_medicine_ner

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