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语法错误数据增强

针对行业语法错误数据稀缺问题,提出语法错误替换方法,可以根据领域的数据进行语法错误制作,定制化行业模型。 目前支持缺字漏字、错别字错误、缺少标点、错用标点、主语不明、谓语残缺、宾语残缺、其他成分残缺、主语多余、虚词多余、其他成分多余、语序不当、动宾搭配不当、其他搭配不当等14种细粒度错误类型的替换。如下图所示: image

也可以对一个句子进行多种错误的替换,如下:

image

模型文件下载

pre_model下的ltp_small,下载地址:https://huggingface.co/LTP/small

获得2024CCL Task7 一等奖

2024CCL Task7: https://github.com/cubenlp/2024CCL_CEFE

博客经验分享:https://www.cnblogs.com/twnlp/p/18208637

评测论文:待发表

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Release files for GrammarEnhancer 1.1

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Source distribution for GrammarEnhancer 1.1
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GrammarEnhancer-1.1-py3-none-any.whl Python 3 none any Details

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