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增加了 证券知识图谱,NLP比赛方案汇总,bert-based语言模型
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README.md

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**124\. 基于TensorFlow和BERT的管道式实体及关系抽取** [github](https://github.com/yuanxiaosc/Entity-Relation-Extraction)
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- Entity and Relation Extraction Based on TensorFlow and BERT. 基于TensorFlow和BERT的管道式实体及关系抽取,2019语言与智能技术竞赛信息抽取任务解决方案。Schema based Knowledge Extraction, SKE 2019
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**125\. 一个小型的证券知识图谱/知识库** [github](https://github.com/lemonhu/stock-knowledge-graph)
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**126\. 复盘所有NLP比赛的TOP方案** [github](https://github.com/zhpmatrix/nlp-competitions-list-review)
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**127\. OpenCLaP:多领域开源中文预训练语言模型仓库** [github](https://github.com/thunlp/OpenCLaP)
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包含如下语言模型及百度百科数据
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- 民事文书BERT bert-base 全部民事文书 2654万篇文书 22554词 370MB
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- 刑事文书BERT bert-base 全部刑事文书 663万篇文书 22554词 370MB
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- 百度百科BERT bert-base 百度百科 903万篇词条 22166词 367MB

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