Source code and dataset for the ACL 2019 paper "GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification".
Please make sure your environment includes:
python (tested on 3.6.7)
pytorch (tested on 1.0.0)
Then, run the command:
pip install -r requirements.txt
We use the codes from Athene UKP TU Darmstadt in the document retrieval and sentence selection steps.
Our evidence extraction results can be found in Tsinghua Cloud or Google Cloud.
Download these files and put them in the data/retrieved/ folder. Then the folder will look like
data/retrieved/
train.ensembles.s10.jsonl
dev.ensembles.s10.jsonl
test.ensembles.s10.jsonl
# Download the fever database
wget -O data/fever/fever.db https://s3-eu-west-1.amazonaws.com/fever.public/wiki_index/fever.db
# Extract the evidence from database
cd scripts/
#drqa一直裝不好
python retrieval_to_bert_input.py
# Build the datasets for gear
#路徑有問題
python build_gear_input_set.py
cd ..
First download our pretrained BERT-Pair model (Tsinghua Cloud or Google Cloud) and put the files into the pretrained_models/BERT-Pair/ folder.
Then the folder will look like this:
pretrained_models/BERT-Pair/
pytorch_model.bin
vocab.txt
bert_config.json
Then run the feature extraction scripts.
cd feature_extractor/
#sh取代下面
chmod +x *.sh
./train_extracor.sh
#IndexError: list index out of range
./dev_extractor.sh
#FileNotFoundError: [Errno 2] No such file or directory: '../data/gear/gear-dev-set-0_001.tsv'
./test_extractor.sh
#FileNotFoundError: [Errno 2] No such file or directory: '../data/gear/gear-test-set-0_001.tsv'
cd ..
cd gear
CUDA_VISIBLE_DEVICES=0 python train.py
#前面沒有設好 所以路徑有問題
cd ..
cd gear
CUDA_VISIBLE_DEVICES=0 python test.py
#前面沒有設好 所以路徑有問題
cd ..
cd gear
python results_scorer.py
#前面沒有設好 所以路徑有問題
cd ..
If you use the code, please cite our paper:
@inproceedings{zhou2019gear,
title={GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification},
author={Zhou, Jie and Han, Xu and Yang, Cheng and Liu, Zhiyuan and Wang, Lifeng and Li, Changcheng and Sun, Maosong},
booktitle={Proceedings of ACL 2019},
year={2019}
}