XBE

Codes and datasets for our paper "Cross-stitching Text and Knowledge Graph Encoders for Distantly Supervised Relation Extraction" (EMNLP 2022)

Overview of XBE

Setup

Install dependencies (consider using a virtual environment):

pip install -r requirements.txt

Then, follow the instruction to install apex.

1.Dataset:

We provide preprocessed NYT10 and Medline21.

Please download them from here: NYT10 (i.e., nyt.zip) and Medline21 (i.e., bio.zip), and unzip them under data/

2.Pre-trained KG Encoder:

Please download our pre-trained KG encoders from: NYT10 KG enc. and Medline21 KG enc., and put them under code_xbe/xbe/ckpt_kg/

3.Train:

Run the following script for training XBE on NYT10.

cd code_xbe/xbe/
bash train_xbe_nyt.sh

Run the following script for training XBE on Medline21.

cd code_xbe/xbe/
bash train_xbe_bio.sh

If you want to directly utilize our pre-trained XBE models, you can download them from: NYT10 XBE and Medline21 XBE, and put them under save/nyt/ and save/bio/ respectively.

4.Test:

Please run the following script for testing the trained XBE model on NYT10 and Medline21 datasets respectively.

cd code_xbe/xbe/
bash test_xbe_nyt.sh

cd code_xbe/xbe/
bash test_xbe_bio.sh

Ablation Study:

Please run the following script for training and testing the XBE model without the cross-stitch mechanism.
```
cd code_xbe/xbe/
bash train_test_xbe_nyt_wo_xstitch.sh
bash train_test_xbe_bio_wo_xstitch.sh
```

Run the following script for the XBE model without Text encoder.

cd code_xbe/xbe/
bash train_test_xbe_nyt_wo_tx.sh
bash train_test_xbe_bio_wo_tx.sh

Run the following script for the XBE model without KG encoder.

cd code_xbe/xbe/
bash train_test_xbe_nyt_wo_kg.sh
bash train_test_xbe_bio_wo_kg.sh

Run the following script for the XBE model with frozen KG encoder.

cd code_xbe/xbe/
bash train_test_xbe_nyt_freeze_kg.sh
bash train_test_xbe_bio_freeze_kg.sh

Run the following script for the XBE model with the KG encoder that is randomly initialized.

cd code_xbe/xbe/
bash train_test_xbe_nyt_random_kg.sh
bash train_test_xbe_bio_random_kg.sh

xiaosonggege/xbe

XBE