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Joint Extraction of Entities and Relations Based on cnn+rnn

Results 9 Joint-Extraction-of-Entities-and-Relations-Based-on-a-Novel-Tagging-Scheme issues
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我在跑这个模型是,发现少了一个train.json文件,请问下,这个是字母得到的。我看文件里面是没有这个的,train.txt也没有 ![image](https://user-images.githubusercontent.com/88226175/178959745-4c9d021f-087a-4525-bb57-7afb719b98bf.png)

I converted the dataset to Chinese dataset but there was an error. Traceback (most recent call last): File "E:/PycharmProjects/LSTM_LSTM_Bias/train.py", line 276, in train() File "E:/PycharmProjects/LSTM_LSTM_Bias/train.py", line 168, in train loss...

Is it an error, or was it implemented like this for simplification purposes? Paper: ![imagen](https://user-images.githubusercontent.com/30293331/120087979-bebffc80-c0ec-11eb-90aa-20b9991f5949.png) Code: https://github.com/gswycf/Joint-Extraction-of-Entities-and-Relations-Based-on-a-Novel-Tagging-Scheme/blob/78b664f0007e0668e16e679ff11522ad660d4f40/model.py#L64-L79

There is a mistake in the 206 row in predict.py 206 temp[relation_label][int(role) - 1].append(idx) if pos == "B" or pos == "S": if relation_label not in temp: temp[relation_label] = [[],...

I read the data.py and found that seems overlaps of tags are just counted but not used in sentence tag. After data precessing, there are a hug number of overlap....