ner_corpus_chinese's Introduction

NER_corpus_chinese

可获取的ENR中文语料

目前网络上流传比较广泛的主要是以下几个：

人民日报1998版本：其实就是分词的训练语料，将其中/t、/nr、/ns、/nt看做实体标签就可以做NER了。
MSRA语料：以BIO格式标注了人名、地名、组织机构名三类实体。
玻森NLP语料：包含2000个段落，标注了6类实体，除了时间和3种常见类别外，还有公司名和产品名。但规模小，只有1MB多点。

其他可能用来研究的语料：

人民日报2014版：标注格式跟1998版有较大变化，词性分得更细致，实体标注有嵌套关系。规模大了不少，有1750万字左右，但需要较为复杂的预处理。
不知名语料：以BIO格式标注了人名、地名、组织机构名三类实体。130多万字

不应公开传播的垂直域NER语料：

CCKS2017电子病历实体标注： https://github.com/napoler/CCKS-2017-task2

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