Requirements

• Tensorflow=1.2.0
• jieba=0.37

Basic Usage

Default parameters:

• batch size: 20
• gradient clip: 5
• embedding size: 100
• optimizer: Adam
• dropout rate: 0.5
• learning rate: 0.001

Train the model with default parameters:

$ python3 main.py --train=True --clean=True

Online evaluate:

$ python3 main.py
$ python3 muba_KG_new_new. py

Explain

The project consists of two parts, one is named entity recognition (execute main. py), which includes the basic crf+BILSTM, and the addition of the attachment network and the highway network on this basis, and the other is knowledge map construction (install Neo4j in advance, create an empty database, use python to construct the knowledge graph, and execute muba_KG_new_new. py).

Because of the medical electronic medical record, no data set is provided in the code.