Comments (2)
Thanks for your interest.
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Using the entire FB2M would be too slow. A rough method is used to filter a small portion, i.e., if a fact's entities and predicate do not contain any words in the questions, then we remove them. Actually embedding more completed knowledge graphs would better support the KG embedding based method. So, it is fair.
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In FreeBase, there are some facts share the same head entity and predicate, but with different tail entities. It is easy to search them.
Thanks.
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I see. Thank you for your reply!
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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
- An Issue about the Statistics of FB2M and FB5M 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
- File Not Found Error.
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