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View Code? Open in Web Editor NEWCode & data accompanying the NAACL 2019 paper "Bidirectional Attentive Memory Networks for Question Answering over Knowledge Bases"
License: Apache License 2.0
Code & data accompanying the NAACL 2019 paper "Bidirectional Attentive Memory Networks for Question Answering over Knowledge Bases"
License: Apache License 2.0
Hi! just trying to transfer your model to another dataset and KB, for the file entity2id.json/ entityType2id.json/ relation2id.json, is there any restrictions on assigining their IDs? Or just assigining a distinct ID to each relation/entity is OK?
the code:
ret = process.extract(topic_ent.replace('_', ' '), set(list(zip(*ent_types))[0]), scorer=fuzz.token_sort_ratio)
how to solve it please?
Running any of the commands from the readme gives: FileNotFoundError: [Errno 2] No such file or directory: '../data/WebQ/train.json'
even though this file is not mentioned in the config and does not exist in the pretrained model. This file is probably hardcoded and the filename from the config should be used instead.
Hello! Is there any support for testing the model on new questions after training it? If not, how would you recommend going about building that functionality? Ideally I would like to deploy the model as an API.
Hi, I just read your paper and find it very interesting. I want to try running the code but it seems you haven't uploaded it yet. May I know if you have any update plan?
Hello! I download your dataste. The train/test/valid files (raw_train.json/raw_valid.json/raw_test.json) both contain the "freebaseKeyCands" data. Where does the data "freebaseKeyCands" come from? It is the entity linking results by using Freebase Search API ? Could you provide the entity linking results by using Freebase Search API for me ? Thanks a lot.
when i run train_entnet.py, i met a problem :
Traceback (most recent call last):
File "train_entnet.py", line 43, in <module>
[valid_memories, valid_queries, valid_query_lengths], valid_ent_inds)
File "/home/jzw/NLP/kbqa/BAMnet/src/core/bamnet/entnet.py", line 96, in train
train_loss += self.train_step(batch_xs, batch_ys) / num_batches
File "/home/jzw/NLP/kbqa/BAMnet/src/core/bamnet/entnet.py", line 174, in train_step
loss.backward()
File "/home/jzw/python3/lib/python3.6/site-packages/torch/tensor.py", line 93, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph)
File "/home/jzw/python3/lib/python3.6/site-packages/torch/autograd/__init__.py", line 90, in backward
allow_unreachable=True) # allow_unreachable flag
RuntimeError: CuDNN error: CUDNN_STATUS_INTERNAL_ERROR
i use torch 0.4.1, cuda 8, cudnn 7, how can i fix it?
Thank you.
the preprocessed data and the pretrained models can't be downloaded
Hello, I can't visit onedrive website. Can you provide data and models in other ways, such as Google drive
You gave a link of your research data. I downloaded it and I saw a file called freebase_full.json. In this file, each element has its neighbors and paths directing to them. I checked the freebase dump which offered by google with sparql language, the paths that each element connects in your json file are not the all. Which means there are more paths should be connected by each element in freebase_full.json. I’m curious about how did you decide which path or neighbor should be added in each record? How did you build freebase_full.json file?
All the best, appreciate!
Siqi Lai
Hi,
Thank you for your great work. I'm trying to run your code on FreebaseQA. Could you provide the freebase key file
?
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