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Source code for "UniRE: A Unified Label Space for Entity Relation Extraction.", ACL2021. It is based on our NERE toolkit (https://github.com/Receiling/NERE).
License: MIT License
当我训练SciERC时,发生如下错误,有人遇到过吗?
[2021-12-30 12:30:40,742 - entity_relation_joint_decoder.py - line:274 - INFO]: Load bert tokenizer successfully.
Traceback (most recent call last):
File "C:\Users\Administrator\Desktop\UniRE-master\entity_relation_joint_decoder.py", line 330, in
main()
File "C:\Users\Administrator\Desktop\UniRE-master\entity_relation_joint_decoder.py", line 295, in main
ace_dataset.build_dataset(vocab=vocab,
File "C:\Users\Administrator\Desktop\UniRE-master\inputs\datasets\dataset.py", line 78, in build_dataset
instance_settting['instance'].count_vocab_items(counter,
File "C:\Users\Administrator\Desktop\UniRE-master\inputs\instance.py", line 61, in count_vocab_items
field.count_vocab_items(counter, sentences)
File "C:\Users\Administrator\Desktop\UniRE-master\inputs\fields\token_field.py", line 39, in count_vocab_items
for sentence in sentences:
File "C:\Users\Administrator\Desktop\UniRE-master\inputs\dataset_readers\ace_reader_for_joint_decoding.py", line 37, in iter
state, results = self.get_tokens(line)
File "C:\Users\Administrator\Desktop\UniRE-master\inputs\dataset_readers\ace_reader_for_joint_decoding.py", line 90, in get_tokens
logger.error("article id: {} sentence id: {} doesn't contain 'sentText'.".format(line['articleId'], line['sentId']))
KeyError: 'articleId'
你好,Pre-trained Models 里面的百度网盘链接里面文件没了,可以重新提供一下文件吗?
感谢作者分享的代码,我刚接触实体关系联合抽取任务。
为什么作者在文中提到了overlapping triples,可是不用NYT和WebNLG数据集,而要使用ACE呢?
我也注意到,实体关系联合抽取的文章,一部分用ACE,一部分用NYT,这之间又有什么区别呢?
感谢楼主!
尊敬的作者,您好!
看了您的文章很受启发,但有些疑惑在于,您是怎么做ACE2004数据集上的5-fold交叉验证的,您是在这五个数据集上跑了五次然后取平均值吗?
其次,如果可以的话,希望获取ACE的数据集。([email protected])
祝您工作顺利,平安喜乐!
你好,我想请教一下关于数据集中两个实体之间关系为None的是如何在评估里面处理的?
Thanks for your amazing work!
I do the data-preprocess and train as the guide in the Readme.md
I see the code set the seed for random、torch and np.
I train the model with the SciERC dataset and early stop at epoch 229 , get the result:
I train it with a RTX3090 GPU without any modify the code (same as the Readme.md)
I see, in the paper, the result is:
the F1 for the ent is 68.4 and i get 66.03
How to reproduce the result in the paper?
Sincerely looking forward to your reply!
作者你好,感谢你们开源了代码,代码非常整洁易读。我注意到在论文中你们也提到UniRE无法处理overlap entity的情况,在阅读代码时,我发现这部分包含overlap的entity的句子似乎被直接扔掉了,我是根据
UniRE/entity_relation_joint_decoder.py
Line 281 in 4f59bea
请问作者能分享一下数据集吗,readme没有提供数据集下载方式
When I test on scierc dataset, the following errors are reported: error message:
Traceback (most recent call last):
File "entity_relation_joint_decoder.py", line 330, in <module>
main()
File "entity_relation_joint_decoder.py", line 316, in main
model.load_state_dict(state_dict,False)
File "/home/jsj201-9/anaconda3/envs/unire/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1407, in load_state_dict
self.__class__.__name__, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for EntRelJointDecoder:
size mismatch for embedding_model.bert_encoder.bert_model.embeddings.word_embeddings.weight: copying a param with shapetorch.Size([31090, 768]) from checkpoint, the shape in current model is torch.Size([30522, 768]).
Where is the file 'train.json'
使用如下提供的流程和代码,以及ACE2004数据集进行处理
https://github.com/LorrinWWW/two-are-better-than-one/tree/master/datasets
① 执行python ace2json.py后生成了如下文件
② 执行python unify.py后在unified目录下生成了如下文件:
请问针对您的脚本命令./ace2004.sh ace2004_folder
,以及split.py,我该使用哪一个路径作为ace2004_folder
这一参数?谢谢!
修改shell脚本中的
--device 0
为
--device 0, 1, 2 ,3
会报错,这里是否需要我自己进行实现,还是说如何可以做到? 麻烦您了,谢谢!
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