This code is for ACL2018 paper "Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism"

• python2.7
• requirements.txt

You need to modify the data path in const.py before running the code. The pre-processed data is released.

WebNLG:

• dataset
• pre-trained word embedding

NYT:

• dataset
• origin dataset
• pre-trained word embedding

Or, you can download them (without pre-trained word embedding) in Baidu SkyDrive with code "y286".

python main.py -c config.json -t 0 -cell lstm

The cell can be "gru" or "lstm". You can specify the GPU card number by "-g". For exampe, "python main.py -c config.json -t 0 -cell lstm -g 0".

You need to set the epochs of the model in main.py first. Then run the following commands: python main.py -c config.json -t 1 -cell lstm

"-t 1" means test and "-t 2" means valid.

The data_process can help you understand how did we process the data.