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[AKBC 19] Improving Relation Extraction by Pre-trained Language Representations

Home Page: https://arxiv.org/abs/1906.03088

License: MIT License

Perl 16.86% Python 81.78% Shell 1.36%
information-extraction machine-learning multi-task-learning nlp relation-extraction transformer

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meisin gdsttian vhientran yolymaker amirveyseh ozaddaro gstoica27 dav009 ngo010 p208p2002 miss-ming tekrajchhetri

tre's Issues

dataset issue

Excuse me, how can I get the TACRED dataset or how can I get the LDC publication?
Thank you.

may the model support Chinese?

thx for your sharing of your works on the relation extraction, and i want to know if the project supports the Chinese or not , thx

How to use BERT

Hi,

How do I use BERT with this architecture?
Thank you in advance

ModuleNotFoundError: No module named '_regex'

I downloaded Trained Models to produce your paper results. However, for SemEval2010 Task 8, it is an error when evaluating:

File "/var/autofs/cl/work/TRE-master/train_utils.py", line 97, in load_model
text_encoder = pickle.load(f)
ModuleNotFoundError: No module named '_regex'

The above error is appeared when I try to run this command below:

CUDA_VISIBLE_DEVICES=0 python relation_extraction.py evaluate --dataset semeval_2010_task8 --test-file datasets/semeval_jsonl/semeval_2010_task8/test.jsonl --log-dir logs/ --save-dir logs/official_model/tre_semeval

Please help me to consider this problem. Thank you so much.

UnboundLocalError for Semeval training

The training command works well for the tacred dataset. But it didn't work for the semeval dataset.

I run the command below. datasets/semeval_jsonl stores the data.

python relation_extraction.py train \
  --write-model True \
  --masking-mode grammar_and_ner \
  --batch-size 8 \
  --max-epochs 3 \
  --lm-coef 0.5 \
  --learning-rate 5.25e-5 \
  --learning-rate-warmup 0.002 \
  --clf-pdrop 0.1 \
  --attn-pdrop 0.1 \
  --word-pdrop 0.0 \
  --dataset semeval_2010_task8 \
  --data-dir datasets/semeval_jsonl \
  --seed=0 \
  --log-dir ./logs/

The error shows:

Traceback (most recent call last):
  File "relation_extraction.py", line 453, in <module>
    'evaluate': evaluate
  File "/anaconda3/envs/py36/lib/python3.6/site-packages/fire/core.py", line 127, in Fire
    component_trace = _Fire(component, args, context, name)
  File "/anaconda3/envs/py36/lib/python3.6/site-packages/fire/core.py", line 366, in _Fire
    component, remaining_args)
  File "/anaconda3/envs/py36/lib/python3.6/site-packages/fire/core.py", line 542, in _CallCallable
    result = fn(*varargs, **kwargs)
  File "relation_extraction.py", line 302, in train
    dev_file=dev_file)
  File "/Users/smap10/Project/RE-Task/TRE/datasets/semeval_2010_task8.py", line 113, in fetch
    SemEval2010Task8._load_from_jsonl(join(path_to_data, train_file), is_test=False, masking_mode=masking_mode)
  File "/Users/smap10/Project/RE-Task/TRE/datasets/semeval_2010_task8.py", line 88, in _load_from_jsonl
    example = SemEval2010Task8.apply_masking_mode(example, masking_mode)
  File "/Users/smap10/Project/RE-Task/TRE/datasets/semeval_2010_task8.py", line 259, in apply_masking_mode
    first_entity_replace, second_entity_replace = [f'{g}-{n}' for g, n in zip(grammar_type, ner_type)]
UnboundLocalError: local variable 'grammar_type' referenced before assignment

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