Comments (1)
Hi, thank you very much for sharing the code and data! But I found an issue with the FB2M and FB5M datasets shared in https://www.dropbox.com/s/9lxudhdfpfkihr1/data.zip.
The paper (https://arxiv.org/pdf/1506.02075.pdf) reports the statistics of FB2M and FB5M in Table-2, and it says, for FB2M, No. entities 2,150,604; No. relations 6,701; No. atomic facts 14,180,937; However, in your dataset, for FB2M, No. entities 1,963,130; No. relations 6,701; No. atomic facts 14,174,246;
So, there are differences between the No. entities and No. triples of your data and the reported statistics (issue found in both FB2M and FB5M). I don't know if you have also noticed this issue.
Please bear with me if I made a mistake. Many thanks!
Have you solved this problem? If so, why?
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Related Issues (20)
- Issue with train_entity.py HOT 1
- train_entity.py 头实体表示学习模型训练精度只有63 HOT 26
- Prediction on a Custom Dataset HOT 4
- the data cannot be downloaded HOT 1
- TypeError: can’t convert cuda:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first HOT 6
- Problem in beginning the training
- FileNotFoundError: [Errno 2] No such file or directory: 'preprocess/dete_best_model.pt' HOT 3
- ValueError: cannot reshape array of size 161914250 into shape (647639,250) HOT 4
- The KG used in train_entity.py appears to be smaller HOT 1
- Reproducability
- Test on FB2M HOT 1
- 请问这些文件我并没有在下载中找到这些preprocess/train.txt,preprocess/valid.txt文件,请问可以在哪里获得这些文件呢?谢谢
- 代码里面有这个实体的人工校正,是因为freebase的数据集的问题吗?或者是其他原因?求救~
- 老师您好,我最近在更换其他的数据集来实现这个代码。您可以将python3.6 transE_emb.py --learning_rate 0.003 --batch_size 3000 --eval_freq 50这个文件提供给我吗?
- Error : ImportError: /usr/lib/x86_64-linux-gnu/libstdc++.so.6: version `GLIBCXX_3.4.26' not found (required by /Data/komal/anaconda3/envs/pyg/lib/python3.8/site-packages/scipy/linalg/_matfuncs_sqrtm_triu.cpython-38-x86_64-linux-gnu.so)
- IndexError: index out of range in self
- an error
- I have some confusions,Can you help me? HOT 2
- File Not Found Error.
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