Code for Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works

Related tags

Deep Learning event-extraction prompt-based constrained-sequence-generation
Overview

GDAP

Code for Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works

Environment

  • Python (verified: v3.8)
  • CUDA (verified: v11.1)
  • Packages (see requirements.txt)

Usage

Preprocessing

We follow dygiepp for data preprocessing.

  • text2et: Event Type Detection
  • ettext2tri: Trigger Extraction
  • etrttext2role: Argument Extraction
# data processed by dyieapp
data/text2target/dyiepp_ace1005_ettext2tri_subtype
├── event.schema 
├── test.json
├── train.json
└── val.json

# data processed by  data_convert.convert_text_to_target
data/text2target/dyiepp_ace1005_ettext2tri_subtype
├── event.schema
├── test.json
├── train.json
└── val.json

Useful commands:

python -m data_convert.convert_text_to_target # data/raw_data -> data/text2target
python convert_dyiepp_to_sentence.py data/raw_data/dyiepp_ace2005 # doc -> sentence, used in evaluation

Training

Relevant scripts:

  • run_seq2seq.py: Python code entry, modified from the transformers/examples/seq2seq/run_seq2seq.py
  • run_seq2seq_span.bash: Model training script logging to the log file.

Example (see the above two files for more details):

# ace05 event type detection t5-base, the metric_format use eval_trigger-F1 
bash run_seq2seq_span.bash --data=dyiepp_ace2005_text2et_subtype --model=t5-base --format=et --metric_format=eval_trigger-F1

# ace05 tri extraction t5-base
bash run_seq2seq_span.bash --data=dyiepp_ace2005_ettext2tri_subtype --model=t5-base --format=tri --metric_format=eval_trigger-F1

# ace05 argument extraction t5-base
bash run_seq2seq_span.bash --data=dyiepp_ace2005_etrttext2role_subtype --model=t5-base --format=role --metric_format=eval_role-F1

Trained models are saved in the models/ folder.

Evaluation

  • run_tri_predict.bash: trigger extraction evaluation and inference script.
  • run_arg_predict.bash: argument extraction evaluation and inference script.

Todo

We aim to expand the codebase for a wider range of tasks, including

  • Name Entity Recognition
  • Keyword Generation
  • Event Relation Identification

If you find this repo helpful...

Please give us a ⭐ and cite our paper as

@misc{si2021-GDAP,
      title={Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works}, 
      author={Jinghui Si and Xutan Peng and Chen Li and Haotian Xu and Jianxin Li},
      year={2021},
      eprint={2110.04525},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

This project borrows code from Text2Event

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Comments
  • Event type extraction inference

    Event type extraction inference

    I have finished the training of Entity type extraction task, and I have a file with raw text and no event label, I wondered how to get the entity type inference?

    opened by AndDoIt 4
  • 关于约束解码的一个问题

    关于约束解码的一个问题

    作者您好，关于约束解码我有一个问题，请问constraint_decoder为什么只在下面代码条件下使用，希望作者能够解答我的疑问，谢谢！

    https://github.com/RingBDStack/GDAP/blob/f6acafafd473cd1ccb57d79aaf95be14de7646fd/seq2seq/constrained_seq2seq.py#L145-L152

    opened by hlee-top 2
  • Wrong arguments for the ET task.

    Wrong arguments for the ET task.

    https://github.com/RingBDStack/GDAP/blob/main/README.md#training The script to train the et model is wrong. The argument format should be et not tri. The tri would gave poor performance.

    opened by littlefive5 2
  • [Clean code] 缺少函数TreePredictParser, SpanPredictParser, RTRolePredictParser

    [Clean code] 缺少函数TreePredictParser, SpanPredictParser, RTRolePredictParser

    你好，我在运行run_tri_predict.bash的时候报错，检查之后发现evaluation.py这个文件的第9行 from extraction.predict_parser.target_predict_parser import TreePredictParser, SpanPredictParser, RTRolePredictParser, RolePredictParser, TriPredictParser 导入时提示缺少函数TreePredictParser, SpanPredictParser, RTRolePredictParser 1635586363(1) 我查找之后发现，在target_predict_parser.py这个文件中并没有这几个函数

    opened by waow123 2
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