Installation

For training, a GPU is recommended to accelerate the training speed.

PyTroch

The code is based on PyTorch 1.6+. You can find tutorials here.

Usage

• Run the full model on SemEval dataset with default hyperparameter settings
  

python3 src/train.py

Data

Format

Each dataset is a folder under the ./data folder:

./data
└── SemEval
    ├── train_sentence.json
    ├── train_label_id.json
    ├── dev_sentence.json
    ├── dev_label_id.json
    ├── test_sentence.json
    └── test_label_id.json

Download

• SemEval: SemEval 2010 Task 8 data (included in data/SemEval)
  
• TACRED: The TAC Relation Extraction Dataset (download)
  

Then use the scripts from data/data_prepare.py to further preprocess the data. For SemEval, the script split the original training data into two sets. For TACRED, the script first perform some preprocessing to ensure the same format as SemEval.