Large Language Models Enhanced Automatic Knowledge Graphs Generation

Application

Steps to run the application:

1. Activate a virtual environment

sudo apt install python3.8-venv
python3 -m venv venv
source venv/bin/activate

2. Navigate to the app directory:

cd app/

3. Install requirements

pip3 install -r requirements.txt

4. Start the application

streamlit run to_kg_app.py

In order to generate a knowledge graph from text you need to have an OpenAI API key.

Scripts

Steps to start the script:

1. Activate a virtual environment

sudo apt install python3.8-venv
python3 -m venv venv
source venv/bin/activate

2. Navigate to the scripts directory:

cd scripts

Generate a KG from an input text

1. Navigate to the textToKG directory

cd textToKG/

2. Install requirements

pip3 install -r requirements.txt

3. Run the script by providing your Open AI API key as the first parameter

python ./toKG.py <input_dir.txt> <output_dir.ttl>  <YOUR_API_KEY>

Run a deduplication of your KG

1. Navigate to the deduplication directory

cd deduplication/

2. Install requirements

pip3 install -r requirements.txt

3. Run the deduplication script.

python ./deduplication.py <input_file.ttl> <output_file.ttl>

The deduplication step requires user interaction. It is based on python's dedupe library (https://docs.dedupe.io/en/latest/). After running the script you will receive multiple questions about deduplicated statements in your knowledge graph.

License

Shield:

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

CC-BY-SA cite as: Vasil Vasilev, Georgi Grazhdanski, Sylvia Vassileva, Ivan Koychev and Svetla Boytcheva. (2024) Large language models enhanced automatic knowledge graphs generation in medical domain. It was submitted to ESWC 2024