Comments (1)
Thanks for your interest. Yes, you are right. Not every head and tail entity in SimpleQuestions is included in entity2id.txt. There are three reasons.
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Not all the entities have been included in FB2M or FB5M. FB2M or FB5M are just subsets of Freebase.
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In question answering, we don't know the head and tail entities of the questions. Otherwise, it is cheating. What we could do is to try the best to guess all possible entities.
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FB2M or FB5M is too large to perform knowledge graph embedding on the 16GB GPU. Thus, we use a heuristic method to select partial entities.
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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
- I have some confusions,Can you help me? HOT 2
- File Not Found Error.
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