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Deprecated!

The maintenance of this project has moved to the AllenNLP framework.
Where you can use the model and an online demo. This thin wrapper may also be useful if you want to run the pretrained model.

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supervised-oie

Code for training a supervised Neural Open IE model, as described in our NAACL2018 paper.
๐Ÿšง Still under construction ๐Ÿšง

Citing ๐Ÿ”–

If you use this software, please cite:

@InProceedings{Stanovsky2018NAACL,
  author    = {Gabriel Stanovsky and Julian Michael and Luke Zettlemoyer and Ido Dagan},
  title     = {Supervised Open Information Extraction},
  booktitle = {Proceedings of The 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT)},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {(to appear)},
}

Quickstart ๐Ÿฃ

  1. Install requirements ๐Ÿ™‡
pip install requirements.txt
  1. Download embeddings ๐Ÿšถ
cd ./pretrained_word_embeddings/
./download_external.sh
  1. Train model ๐Ÿƒ
cd ./src
python  ./rnn/confidence_model.py  --train=../data/train.conll  --dev=../data/dev.conll  --test=../data/test.conll --load_hyperparams=../hyerparams/confidence.json```

NOTE: Models are saved by default to the models dir, unless a "--saveto" command line argument is passed. See confidence_model.py for more details.

  1. Predict with a trained model ๐Ÿ‘
python ./trained_oie_extractor.py \
    --model=path/to/model \
    --in=path/to/raw/sentences
    --out=path/to/output/file
    --conll

More scripts ๐Ÿšด

See src/scripts for more handy scripts. Additional documentation coming soon!

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Code for training a Neural Open IE model (NAACL2018)

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