Combining Distant and Direct Supervision for Neural Relation Extraction
This is code for our NAACL 2019 paper on combining distant and direct supervision to improve relation extraction. The code is implemented using PyTorch and AllenNLP.
After cloning this repository, follow the steps below for training and prediction.
pip install -r requirements.txt
./scripts/train.sh serialization_dir
allennlp predict serialization_dir/model.tar.gz tests/fixtures/data.txt --include-package relex --cuda-device 0 --batch-size 32 --use-dataset-reader --predictor relex --output-file predictions.json
predictions.json
contains model predictions for the examples provided in tests/fixtures/data.txt
@inproceedings{Beltagy2019Comb,
title={Combining Distant and Direct Supervision for Neural Relation Extraction},
author={Iz Beltagy and Kyle Lo and Waleed Ammar},
year={2019},
booktitle={NAACL}
}