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tplinker-ner's Issues

关于扩充标签库后数据标注的问题

请问对一个已有标注的ner数据集，若采用扩充后的标签库，其对应的handshaking矩阵具体是什么形式呢？
扩充后标签库的部分标签与实体关系有关，但是ner数据集上没有主语或宾语等标注。那涉及到标签库该类标签时，handshaking矩阵对应坐标的值是多少呢？
例如有个输入文本“小明去北京”。包含两个实体类型“人名”和“地名”，其对应标签库有10个标签。其中标签“人名-SH to OH”的含义是“人名关系下主语的头到宾语的头”，ner标注中并没有包含这样的信息，那handshaking矩阵对应坐标的值应该为0吗？
如果handshaking矩阵对应坐标确实为0的话，那矩阵是不是有点太稀疏了？
如果可以解答一二，感激不尽。

换成自己的数据集之后全是0

你好！请问换成自己的数据集之后训练结果全是0可能会是什么原因，我的数据集格式是完全符合要求的，不过标签不一样，需要修改代码吗？在哪里改标签的代码？谢谢解答！

请问损失函数的选择这里可以请教一下吗？

您引用的苏神文章里写的是多标签分类问题，我不太理解实体抽取算法为什么算作是多标签分类问题？
抱歉我是初学者。按照我的理解在矩阵中给两个位置加一个标签，最后得到的也是单个的一种类型而不是多个不是吗？

打扰了！你的作品对我帮助很大，希望可以多多学习！

Could you please provide the macro F1 score?

Thanks for your work. The repo for CLUENER2020 presents the F1 score on each entity class and the macro F1 score over them, while it seems that your 0.9111 is the micro F1 score, Could you please provide the macro F1 score (and the F1 score on each entity class) so that we can see the improvement more clearly?

结果全为0

你好，我把项目下载重新run，发现结果全为0 ，这是怎么回事啊？用得是你的数据集。

英文数据集

请问换成英文数据集的话，token_span和char_span是以字符为单位呢，还是以单词为单位呢
如：Tom：字符为单位，索引是[0,2]；单词为单位是[0,0]

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